A B C D E F G H I J K L M N O P Q R S T U V W Y Z

A

AbstractCandidateItemsStrategy - Class in org.apache.mahout.cf.taste.impl.recommender
Abstract base implementation for retrieving candidate items to recommend
AbstractCandidateItemsStrategy() - Constructor for class org.apache.mahout.cf.taste.impl.recommender.AbstractCandidateItemsStrategy
 
AbstractCluster - Class in org.apache.mahout.clustering
 
AbstractCluster() - Constructor for class org.apache.mahout.clustering.AbstractCluster
 
AbstractCluster(Vector, int) - Constructor for class org.apache.mahout.clustering.AbstractCluster
 
AbstractCluster(Vector, Vector, int) - Constructor for class org.apache.mahout.clustering.AbstractCluster
 
AbstractDataModel - Class in org.apache.mahout.cf.taste.impl.model
Contains some features common to all implementations.
AbstractDataModel() - Constructor for class org.apache.mahout.cf.taste.impl.model.AbstractDataModel
 
AbstractDifferenceRecommenderEvaluator - Class in org.apache.mahout.cf.taste.impl.eval
Abstract superclass of a couple implementations, providing shared functionality.
AbstractDifferenceRecommenderEvaluator() - Constructor for class org.apache.mahout.cf.taste.impl.eval.AbstractDifferenceRecommenderEvaluator
 
AbstractDifferenceRecommenderEvaluator.PreferenceEstimateCallable - Class in org.apache.mahout.cf.taste.impl.eval
 
AbstractDifferenceRecommenderEvaluator.PreferenceEstimateCallable(Recommender, long, PreferenceArray, AtomicInteger) - Constructor for class org.apache.mahout.cf.taste.impl.eval.AbstractDifferenceRecommenderEvaluator.PreferenceEstimateCallable
 
AbstractFactorizer - Class in org.apache.mahout.cf.taste.impl.recommender.svd
base class for Factorizers, provides ID to index mapping
AbstractFactorizer(DataModel) - Constructor for class org.apache.mahout.cf.taste.impl.recommender.svd.AbstractFactorizer
 
AbstractIDMigrator - Class in org.apache.mahout.cf.taste.impl.model
 
AbstractIDMigrator() - Constructor for class org.apache.mahout.cf.taste.impl.model.AbstractIDMigrator
 
AbstractItemSimilarity - Class in org.apache.mahout.cf.taste.impl.similarity
 
AbstractItemSimilarity(DataModel) - Constructor for class org.apache.mahout.cf.taste.impl.similarity.AbstractItemSimilarity
 
AbstractJDBCComponent - Class in org.apache.mahout.cf.taste.impl.common.jdbc
A helper class with common elements for several JDBC-related components.
AbstractJDBCComponent() - Constructor for class org.apache.mahout.cf.taste.impl.common.jdbc.AbstractJDBCComponent
 
AbstractJDBCIDMigrator - Class in org.apache.mahout.cf.taste.impl.model
Implementation which stores the reverse long-to-String mapping in a database.
AbstractJDBCIDMigrator(DataSource, String, String) - Constructor for class org.apache.mahout.cf.taste.impl.model.AbstractJDBCIDMigrator
 
AbstractJob - Class in org.apache.mahout.common
Superclass of many Mahout Hadoop "jobs".
AbstractJob() - Constructor for class org.apache.mahout.common.AbstractJob
 
AbstractLongPrimitiveIterator - Class in org.apache.mahout.cf.taste.impl.common
 
AbstractLongPrimitiveIterator() - Constructor for class org.apache.mahout.cf.taste.impl.common.AbstractLongPrimitiveIterator
 
AbstractNaiveBayesClassifier - Class in org.apache.mahout.classifier.naivebayes
Class implementing the Naive Bayes Classifier Algorithm
AbstractNaiveBayesClassifier(NaiveBayesModel) - Constructor for class org.apache.mahout.classifier.naivebayes.AbstractNaiveBayesClassifier
 
AbstractOnlineLogisticRegression - Class in org.apache.mahout.classifier.sgd
Generic definition of a 1 of n logistic regression classifier that returns probabilities in response to a feature vector.
AbstractOnlineLogisticRegression() - Constructor for class org.apache.mahout.classifier.sgd.AbstractOnlineLogisticRegression
 
AbstractParameter<T> - Class in org.apache.mahout.common.parameters
 
AbstractParameter(Class<T>, String, String, Configuration, T, String) - Constructor for class org.apache.mahout.common.parameters.AbstractParameter
 
AbstractRecommender - Class in org.apache.mahout.cf.taste.impl.recommender
 
AbstractRecommender(DataModel, CandidateItemsStrategy) - Constructor for class org.apache.mahout.cf.taste.impl.recommender.AbstractRecommender
 
AbstractRecommender(DataModel) - Constructor for class org.apache.mahout.cf.taste.impl.recommender.AbstractRecommender
 
AbstractThetaTrainer - Class in org.apache.mahout.classifier.naivebayes.training
 
AbstractThetaTrainer(Vector, Vector, double) - Constructor for class org.apache.mahout.classifier.naivebayes.training.AbstractThetaTrainer
 
AbstractVectorClassifier - Class in org.apache.mahout.classifier
Defines the interface for classifiers that take input as a vector.
AbstractVectorClassifier() - Constructor for class org.apache.mahout.classifier.AbstractVectorClassifier
 
AbstractVectorModelDistribution - Class in org.apache.mahout.clustering.dirichlet.models
 
AbstractVectorModelDistribution() - Constructor for class org.apache.mahout.clustering.dirichlet.models.AbstractVectorModelDistribution
 
AbstractVectorModelDistribution(VectorWritable) - Constructor for class org.apache.mahout.clustering.dirichlet.models.AbstractVectorModelDistribution
 
ABtDenseOutJob - Class in org.apache.mahout.math.hadoop.stochasticsvd
Computes ABt products, then first step of QR which is pushed down to the reducer.
ABtDenseOutJob.ABtMapper - Class in org.apache.mahout.math.hadoop.stochasticsvd
So, here, i preload A block into memory.
ABtDenseOutJob.ABtMapper() - Constructor for class org.apache.mahout.math.hadoop.stochasticsvd.ABtDenseOutJob.ABtMapper
 
ABtDenseOutJob.QRReducer - Class in org.apache.mahout.math.hadoop.stochasticsvd
QR first step pushed down to reducer.
ABtDenseOutJob.QRReducer() - Constructor for class org.apache.mahout.math.hadoop.stochasticsvd.ABtDenseOutJob.QRReducer
 
ABtJob - Class in org.apache.mahout.math.hadoop.stochasticsvd
Computes ABt products, then first step of QR which is pushed down to the reducer.
ABtJob.ABtMapper - Class in org.apache.mahout.math.hadoop.stochasticsvd
So, here, i preload A block into memory.
ABtJob.ABtMapper() - Constructor for class org.apache.mahout.math.hadoop.stochasticsvd.ABtJob.ABtMapper
 
ABtJob.QRReducer - Class in org.apache.mahout.math.hadoop.stochasticsvd
QR first step pushed down to reducer.
ABtJob.QRReducer() - Constructor for class org.apache.mahout.math.hadoop.stochasticsvd.ABtJob.QRReducer
 
accum - Variable in class org.apache.mahout.math.hadoop.stochasticsvd.ABtJob.QRReducer
 
accum - Variable in class org.apache.mahout.math.hadoop.stochasticsvd.BtJob.OuterProductCombiner
 
accum - Variable in class org.apache.mahout.math.hadoop.stochasticsvd.BtJob.OuterProductReducer
 
accumDots(int, double, double[]) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.Omega
 
accumDots(int, double, Vector) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.Omega
 
accumSize - Variable in class org.apache.mahout.math.hadoop.stochasticsvd.ABtDenseOutJob.QRReducer
 
accumSize - Variable in class org.apache.mahout.math.hadoop.stochasticsvd.ABtJob.QRReducer
 
accumulate(IntArrayList, long) - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth2.FPTree
Adds an itemset with the given occurrance count.
accumulate(List<Integer>, long) - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth2.FPTree
Adds an itemset with the given occurrance count.
accumulate(long) - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth2.FPTree.FPNode
 
AdaptiveLogisticRegression - Class in org.apache.mahout.classifier.sgd
This is a meta-learner that maintains a pool of ordinary OnlineLogisticRegression learners.
AdaptiveLogisticRegression() - Constructor for class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression
 
AdaptiveLogisticRegression(int, int, PriorFunction) - Constructor for class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression
Uses AdaptiveLogisticRegression.DEFAULT_THREAD_COUNT and AdaptiveLogisticRegression.DEFAULT_POOL_SIZE
AdaptiveLogisticRegression(int, int, PriorFunction, int, int) - Constructor for class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression
 
AdaptiveLogisticRegression.TrainingExample - Class in org.apache.mahout.classifier.sgd
 
AdaptiveLogisticRegression.TrainingExample(long, String, int, Vector) - Constructor for class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression.TrainingExample
 
AdaptiveLogisticRegression.Wrapper - Class in org.apache.mahout.classifier.sgd
Provides a shim between the EP optimization stuff and the CrossFoldLearner.
AdaptiveLogisticRegression.Wrapper() - Constructor for class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression.Wrapper
 
AdaptiveLogisticRegression.Wrapper(int, int, PriorFunction) - Constructor for class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression.Wrapper
 
AdaptiveWordValueEncoder - Class in org.apache.mahout.vectorizer.encoders
Encodes words into vectors much as does WordValueEncoder while maintaining an adaptive dictionary of values seen so far.
AdaptiveWordValueEncoder(String) - Constructor for class org.apache.mahout.vectorizer.encoders.AdaptiveWordValueEncoder
 
add(long) - Method in class org.apache.mahout.cf.taste.impl.common.FastIDSet
 
add(int[], int[]) - Static method in class org.apache.mahout.classifier.df.data.DataUtils
foreach i : array1[i] += array2[i]
add(int, double) - Method in class org.apache.mahout.classifier.evaluation.Auc
Adds a score to the AUC buffers.
add(int, int) - Method in class org.apache.mahout.classifier.evaluation.Auc
 
add(Integer) - Method in class org.apache.mahout.common.IntegerTuple
add an entry to the end of the list
add(int) - Method in class org.apache.mahout.common.IntTuple
Add an entry to the end of the list
add(String) - Method in class org.apache.mahout.common.StringTuple
add an entry to the end of the list
add(State<T, U>) - Method in class org.apache.mahout.ep.EvolutionaryProcess
 
add(int, long) - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.Pattern
 
addable(long) - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.FrequentPatternMaxHeap
 
addAll(long[]) - Method in class org.apache.mahout.cf.taste.impl.common.FastIDSet
 
addAll(FastIDSet) - Method in class org.apache.mahout.cf.taste.impl.common.FastIDSet
 
addAll(FrequentPatternMaxHeap, int, long) - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.FrequentPatternMaxHeap
 
addChild(int, int) - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.FPTree
 
addChild(int, int) - Method in class org.apache.mahout.fpm.pfpgrowth.TransactionTree
 
addCount(int, long) - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.FPTree
 
addCount(int, long) - Method in class org.apache.mahout.fpm.pfpgrowth.TransactionTree
 
addDatum(double) - Method in class org.apache.mahout.cf.taste.impl.common.FixedRunningAverage
 
addDatum(double) - Method in class org.apache.mahout.cf.taste.impl.common.FullRunningAverage
 
addDatum(double) - Method in class org.apache.mahout.cf.taste.impl.common.FullRunningAverageAndStdDev
 
addDatum(double) - Method in class org.apache.mahout.cf.taste.impl.common.InvertedRunningAverage
 
addDatum(double) - Method in class org.apache.mahout.cf.taste.impl.common.InvertedRunningAverageAndStdDev
 
addDatum(double) - Method in interface org.apache.mahout.cf.taste.impl.common.RunningAverage
 
addDatum(double) - Method in class org.apache.mahout.cf.taste.impl.common.WeightedRunningAverage
 
addDatum(double, double) - Method in class org.apache.mahout.cf.taste.impl.common.WeightedRunningAverage
 
addDatum(double, double) - Method in class org.apache.mahout.cf.taste.impl.common.WeightedRunningAverageAndStdDev
 
addDelta(Vector) - Method in class org.apache.mahout.classifier.discriminative.LinearModel
Update the hyperplane by adding delta.
addDependency(Refreshable) - Method in class org.apache.mahout.cf.taste.impl.common.RefreshHelper
Add a dependency to be refreshed first when the encapsulating object does.
addFlag(String, String, String) - Method in class org.apache.mahout.common.AbstractJob
Add an option with no argument whose presence can be checked for using containsKey method on the map returned by AbstractJob.parseArguments(String[]);
addHeaderCount(int, long) - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.FPTree
 
addHeaderNext(int, int) - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.FPTree
 
addInputOption() - Method in class org.apache.mahout.common.AbstractJob
Add the default input directory option, '-i' which takes a directory name as an argument.
addInstance(String, ClassifierResult) - Method in class org.apache.mahout.classifier.ConfusionMatrix
 
addInstance(String, String) - Method in class org.apache.mahout.classifier.ConfusionMatrix
 
addInstance(double, double) - Method in class org.apache.mahout.classifier.RegressionResultAnalyzer
 
addInstance(String, ClassifierResult) - Method in class org.apache.mahout.classifier.ResultAnalyzer
 
addInteractionToVector(String, String, double, Vector) - Method in class org.apache.mahout.vectorizer.encoders.InteractionValueEncoder
Adds a value to a vector.
addInteractionToVector(byte[], byte[], double, Vector) - Method in class org.apache.mahout.vectorizer.encoders.InteractionValueEncoder
Adds a value to a vector.
addItemPref(long, long, float) - Method in class org.apache.mahout.cf.taste.impl.recommender.slopeone.file.FileDiffStorage
 
addItemPref(long, long, float) - Method in class org.apache.mahout.cf.taste.impl.recommender.slopeone.MemoryDiffStorage
 
addItemPref(long, long, float) - Method in interface org.apache.mahout.cf.taste.recommender.slopeone.DiffStorage
Updates internal data structures to reflect a new preference value for an item.
addModel(OnlineLogisticRegression) - Method in class org.apache.mahout.classifier.sgd.CrossFoldLearner
 
addOption(String, String, String) - Method in class org.apache.mahout.common.AbstractJob
Add an option to the the set of options this job will parse when AbstractJob.parseArguments(String[]) is called.
addOption(String, String, String, boolean) - Method in class org.apache.mahout.common.AbstractJob
Add an option to the the set of options this job will parse when AbstractJob.parseArguments(String[]) is called.
addOption(String, String, String, String) - Method in class org.apache.mahout.common.AbstractJob
Add an option to the the set of options this job will parse when AbstractJob.parseArguments(String[]) is called.
addOption(Option) - Method in class org.apache.mahout.common.AbstractJob
Add an arbitrary option to the set of options this job will parse when AbstractJob.parseArguments(String[]) is called.
addOutputOption() - Method in class org.apache.mahout.common.AbstractJob
Add the default output directory option, '-o' which takes a directory name as an argument.
addPattern(IntArrayList, long) - Method in class org.apache.mahout.fpm.pfpgrowth.TransactionTree
 
addPointToCanopies(Vector, Collection<Canopy>) - Method in class org.apache.mahout.clustering.canopy.CanopyClusterer
This is the same algorithm as the reference but inverted to iterate over existing canopies instead of the points.
addPointToClusters(List<SoftCluster>, Vector) - Method in class org.apache.mahout.clustering.fuzzykmeans.FuzzyKMeansClusterer
 
addPointToNearestCluster(Vector, Iterable<Cluster>) - Method in class org.apache.mahout.clustering.kmeans.KMeansClusterer
Sequential implementation to add point to the nearest cluster
addSample(int, String, double) - Method in class org.apache.mahout.math.stats.GlobalOnlineAuc
 
addSample(int, double) - Method in class org.apache.mahout.math.stats.GlobalOnlineAuc
 
addSample(int, String, double) - Method in class org.apache.mahout.math.stats.GroupedOnlineAuc
 
addSample(int, double) - Method in class org.apache.mahout.math.stats.GroupedOnlineAuc
 
addSample(int, String, double) - Method in interface org.apache.mahout.math.stats.OnlineAuc
 
addSample(int, double) - Method in interface org.apache.mahout.math.stats.OnlineAuc
 
addSpecificOptions() - Method in class org.apache.mahout.graph.linkanalysis.RandomWalkWithRestartJob
 
addText(byte[]) - Method in class org.apache.mahout.vectorizer.encoders.TextValueEncoder
Adds text to the internal word counter, but delays converting it to vector form until flush is called.
addText(CharSequence) - Method in class org.apache.mahout.vectorizer.encoders.TextValueEncoder
Adds text to the internal word counter, but delays converting it to vector form until flush is called.
addToHistory(int, Vector) - Method in class org.apache.mahout.classifier.sgd.RankingGradient
 
addToVector(String, double, Vector) - Method in class org.apache.mahout.vectorizer.encoders.AdaptiveWordValueEncoder
Adds a value to a vector.
addToVector(byte[], double, Vector) - Method in class org.apache.mahout.vectorizer.encoders.ConstantValueEncoder
 
addToVector(byte[], double, Vector) - Method in class org.apache.mahout.vectorizer.encoders.ContinuousValueEncoder
Adds a value to a vector.
addToVector(String, Vector) - Method in class org.apache.mahout.vectorizer.encoders.FeatureVectorEncoder
Adds a value expressed in string form to a vector.
addToVector(byte[], Vector) - Method in class org.apache.mahout.vectorizer.encoders.FeatureVectorEncoder
Adds a value expressed in byte array form to a vector.
addToVector(String, double, Vector) - Method in class org.apache.mahout.vectorizer.encoders.FeatureVectorEncoder
Adds a weighted value expressed in string form to a vector.
addToVector(byte[], double, Vector) - Method in class org.apache.mahout.vectorizer.encoders.FeatureVectorEncoder
 
addToVector(String, double, Vector) - Method in class org.apache.mahout.vectorizer.encoders.InteractionValueEncoder
Adds a value to a vector.
addToVector(byte[], double, Vector) - Method in class org.apache.mahout.vectorizer.encoders.InteractionValueEncoder
Adds a value to a vector.
addToVector(byte[], double, Vector) - Method in class org.apache.mahout.vectorizer.encoders.TextValueEncoder
Adds a value to a vector after tokenizing it by splitting on non-alphanum characters.
addToVector(byte[], double, Vector) - Method in class org.apache.mahout.vectorizer.encoders.WordValueEncoder
Adds a value to a vector.
ADJACENCY_MATRIX - Static variable in class org.apache.mahout.graph.AdjacencyMatrixJob
 
AdjacencyMatrixJob - Class in org.apache.mahout.graph
Distributed computation of the adjacency matrix of a graph, see http://en.wikipedia.org/wiki/Adjacency_matrix
AdjacencyMatrixJob() - Constructor for class org.apache.mahout.graph.AdjacencyMatrixJob
 
adjust(int) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.qr.GivensThinSolver
 
adjustedProbability(VectorWritable, int) - Method in class org.apache.mahout.clustering.dirichlet.DirichletState
return the adjusted probability that x is described by the kth model
AFFINITY_DIMENSIONS - Static variable in interface org.apache.mahout.clustering.spectral.eigencuts.EigencutsKeys
Refers to the dimensions of the raw affinity matrix input.
AFFINITY_PATH - Static variable in interface org.apache.mahout.clustering.spectral.eigencuts.EigencutsKeys
Refers to the Path to the SequenceFile representing the affinity matrix
AffinityMatrixInputJob - Class in org.apache.mahout.clustering.spectral.common
 
AffinityMatrixInputMapper - Class in org.apache.mahout.clustering.spectral.common
Handles reading the files representing the affinity matrix.
AffinityMatrixInputMapper() - Constructor for class org.apache.mahout.clustering.spectral.common.AffinityMatrixInputMapper
 
AffinityMatrixInputReducer - Class in org.apache.mahout.clustering.spectral.common
Tasked with taking each DistributedRowMatrix entry and collecting them into vectors corresponding to rows.
AffinityMatrixInputReducer() - Constructor for class org.apache.mahout.clustering.spectral.common.AffinityMatrixInputReducer
 
age(double, double, double) - Method in class org.apache.mahout.classifier.sgd.ElasticBandPrior
 
age(double, double, double) - Method in class org.apache.mahout.classifier.sgd.L1
 
age(double, double, double) - Method in class org.apache.mahout.classifier.sgd.L2
 
age(double, double, double) - Method in interface org.apache.mahout.classifier.sgd.PriorFunction
Applies the regularization to a coefficient.
age(double, double, double) - Method in class org.apache.mahout.classifier.sgd.TPrior
 
age(double, double, double) - Method in class org.apache.mahout.classifier.sgd.UniformPrior
 
aggregate(double, double) - Method in class org.apache.mahout.math.hadoop.similarity.cooccurrence.measures.CosineSimilarity
 
aggregate(double, double) - Method in class org.apache.mahout.math.hadoop.similarity.cooccurrence.measures.CountbasedMeasure
 
aggregate(double, double) - Method in class org.apache.mahout.math.hadoop.similarity.cooccurrence.measures.EuclideanDistanceSimilarity
 
aggregate(double, double) - Method in interface org.apache.mahout.math.hadoop.similarity.cooccurrence.measures.VectorSimilarityMeasure
 
AggregateAndRecommendReducer - Class in org.apache.mahout.cf.taste.hadoop.item
computes prediction values for each user
AggregateAndRecommendReducer() - Constructor for class org.apache.mahout.cf.taste.hadoop.item.AggregateAndRecommendReducer
 
AggregatorMapper - Class in org.apache.mahout.fpm.pfpgrowth
outputs the pattern for each item in the pattern, so that reducer can group them and select the top K frequent patterns
AggregatorMapper() - Constructor for class org.apache.mahout.fpm.pfpgrowth.AggregatorMapper
 
AggregatorReducer - Class in org.apache.mahout.fpm.pfpgrowth
groups all Frequent Patterns containing an item and outputs the top K patterns containing that particular item
AggregatorReducer() - Constructor for class org.apache.mahout.fpm.pfpgrowth.AggregatorReducer
 
Algorithm - Interface in org.apache.mahout.classifier.bayes
The algorithm interface for implementing variations of bayes Algorithm
allSimilarItemIDs(long) - Method in class org.apache.mahout.cf.taste.impl.similarity.AbstractItemSimilarity
 
allSimilarItemIDs(long) - Method in class org.apache.mahout.cf.taste.impl.similarity.CachingItemSimilarity
 
allSimilarItemIDs(long) - Method in class org.apache.mahout.cf.taste.impl.similarity.file.FileItemSimilarity
 
allSimilarItemIDs(long) - Method in class org.apache.mahout.cf.taste.impl.similarity.GenericItemSimilarity
 
allSimilarItemIDs(long) - Method in interface org.apache.mahout.cf.taste.similarity.ItemSimilarity
 
AllSimilarItemsCandidateItemsStrategy - Class in org.apache.mahout.cf.taste.impl.recommender
returns the result of ItemSimilarity.allSimilarItemIDs(long) as candidate items
AllSimilarItemsCandidateItemsStrategy(ItemSimilarity) - Constructor for class org.apache.mahout.cf.taste.impl.recommender.AllSimilarItemsCandidateItemsStrategy
 
AllUnknownItemsCandidateItemsStrategy - Class in org.apache.mahout.cf.taste.impl.recommender
 
AllUnknownItemsCandidateItemsStrategy() - Constructor for class org.apache.mahout.cf.taste.impl.recommender.AllUnknownItemsCandidateItemsStrategy
 
alpha(double) - Method in class org.apache.mahout.classifier.sgd.CrossFoldLearner
 
alpha(double) - Method in class org.apache.mahout.classifier.sgd.OnlineLogisticRegression
Chainable configuration option.
ALPHA_0_KEY - Static variable in class org.apache.mahout.clustering.dirichlet.DirichletDriver
 
ALPHA_I - Static variable in class org.apache.mahout.classifier.naivebayes.training.ThetaMapper
 
ALPHA_OPTION - Static variable in class org.apache.mahout.clustering.dirichlet.DirichletDriver
 
alphaI() - Method in class org.apache.mahout.classifier.naivebayes.NaiveBayesModel
 
alphaI() - Method in class org.apache.mahout.classifier.naivebayes.training.AbstractThetaTrainer
 
ALSWRFactorizer - Class in org.apache.mahout.cf.taste.impl.recommender.svd
factorizes the rating matrix using "Alternating-Least-Squares with Weighted-λ-Regularization" as described in the paper "Large-scale Collaborative Filtering for the Netflix Prize"
ALSWRFactorizer(DataModel, int, double, int) - Constructor for class org.apache.mahout.cf.taste.impl.recommender.svd.ALSWRFactorizer
 
ANALYZER_CLASS - Static variable in class org.apache.mahout.vectorizer.DocumentProcessor
 
ANALYZER_NAME - Static variable in class org.apache.mahout.vectorizer.EncodingMapper
 
ANALYZER_NAME_OPTION - Static variable in class org.apache.mahout.common.commandline.DefaultOptionCreator
 
analyzerOption() - Static method in class org.apache.mahout.common.commandline.DefaultOptionCreator
Returns a default command line option for specifying a Lucene analyzer class
appendRow(double[]) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.qr.GivensThinSolver
api for row-by-row addition
apply(String, int, Vector, AbstractVectorClassifier) - Method in class org.apache.mahout.classifier.sgd.DefaultGradient
Provides a default gradient computation useful for logistic regression.
apply(String, int, Vector, AbstractVectorClassifier) - Method in interface org.apache.mahout.classifier.sgd.Gradient
 
apply(String, int, Vector, AbstractVectorClassifier) - Method in class org.apache.mahout.classifier.sgd.MixedGradient
 
apply(String, int, Vector, AbstractVectorClassifier) - Method in class org.apache.mahout.classifier.sgd.RankingGradient
 
apply(T, double[]) - Method in interface org.apache.mahout.ep.EvolutionaryProcess.Function
 
apply(double) - Method in class org.apache.mahout.ep.Mapping.Exponential
 
apply(double) - Method in class org.apache.mahout.ep.Mapping.Identity
 
apply(double) - Method in class org.apache.mahout.ep.Mapping.LogLimit
 
apply(double) - Method in class org.apache.mahout.ep.Mapping.SoftLimit
 
applyGivensInPlace(double, double, double[], double[], int, int) - Static method in class org.apache.mahout.math.hadoop.stochasticsvd.qr.GivensThinSolver
 
applyGivensInPlace(double, double, Vector, Vector, int, int) - Static method in class org.apache.mahout.math.hadoop.stochasticsvd.qr.GivensThinSolver
 
applyGivensInPlace(double, double, int, int, Matrix) - Static method in class org.apache.mahout.math.hadoop.stochasticsvd.qr.GivensThinSolver
 
asFormatString(String[]) - Method in class org.apache.mahout.clustering.AbstractCluster
 
asFormatString() - Method in class org.apache.mahout.clustering.canopy.Canopy
 
asFormatString(String[]) - Method in interface org.apache.mahout.clustering.Cluster
Produce a custom, human-friendly, printable representation of the Cluster.
asFormatString(String[]) - Method in class org.apache.mahout.clustering.dirichlet.DirichletCluster
 
asFormatString() - Method in class org.apache.mahout.clustering.fuzzykmeans.SoftCluster
 
asFormatString() - Method in class org.apache.mahout.clustering.kmeans.Cluster
 
asFormatString() - Method in class org.apache.mahout.clustering.meanshift.MeanShiftCanopy
 
assign(HmmModel) - Method in class org.apache.mahout.classifier.sequencelearning.hmm.HmmModel
Assign the content of another HMM model to this one
assignColumn(int, Vector) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.UpperTriangular
 
assignNonZeroElementsInRow(int, double[]) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.UpperTriangular
 
assignRow(int, Vector) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.UpperTriangular
 
assignToModel(VectorWritable) - Method in class org.apache.mahout.clustering.dirichlet.DirichletClusterer
Assign the observation to one of the models based upon probabilities
asString(String) - Method in class org.apache.mahout.vectorizer.encoders.ConstantValueEncoder
 
asString(String) - Method in class org.apache.mahout.vectorizer.encoders.ContinuousValueEncoder
Converts a value into a form that would help a human understand the internals of how the value is being interpreted.
asString(String) - Method in class org.apache.mahout.vectorizer.encoders.FeatureVectorEncoder
Converts a value into a form that would help a human understand the internals of how the value is being interpreted.
asString(String) - Method in class org.apache.mahout.vectorizer.encoders.InteractionValueEncoder
Converts a value into a form that would help a human understand the internals of how the value is being interpreted.
asString(String) - Method in class org.apache.mahout.vectorizer.encoders.TextValueEncoder
Converts a value into a form that would help a human understand the internals of how the value is being interpreted.
asString(String) - Method in class org.apache.mahout.vectorizer.encoders.WordValueEncoder
Converts a value into a form that would help a human understand the internals of how the value is being interpreted.
at(int) - Method in class org.apache.mahout.common.IntTuple
Fetches the string at the given location
attribute(int) - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.FPTree
 
attribute() - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth2.FPTree.FPNode
 
attribute(int) - Method in class org.apache.mahout.fpm.pfpgrowth.TransactionTree
 
attrIterable() - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth2.FPTree
Returns an Iterable over the attributes in the tree, sorted by frequency (low to high).
attrIterableRev() - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth2.FPTree
Returns an Iterable over the attributes in the tree, sorted by frequency (high to low).
Auc - Class in org.apache.mahout.classifier.evaluation
Computes AUC and a few other accuracy statistics without storing huge amounts of data.
Auc(double) - Constructor for class org.apache.mahout.classifier.evaluation.Auc
Allocates a new data-structure for accumulating information about AUC and a few other accuracy measures.
Auc() - Constructor for class org.apache.mahout.classifier.evaluation.Auc
 
auc() - Method in class org.apache.mahout.classifier.evaluation.Auc
Computes the AUC of points seen so far.
auc() - Method in class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression
What is the AUC for the current best member of the population.
auc() - Method in class org.apache.mahout.classifier.sgd.CrossFoldLearner
 
auc() - Method in class org.apache.mahout.math.stats.GlobalOnlineAuc
 
auc() - Method in class org.apache.mahout.math.stats.GroupedOnlineAuc
 
auc() - Method in interface org.apache.mahout.math.stats.OnlineAuc
 
AverageAbsoluteDifferenceRecommenderEvaluator - Class in org.apache.mahout.cf.taste.impl.eval
A RecommenderEvaluator which computes the average absolute difference between predicted and actual ratings for users.
AverageAbsoluteDifferenceRecommenderEvaluator() - Constructor for class org.apache.mahout.cf.taste.impl.eval.AverageAbsoluteDifferenceRecommenderEvaluator
 
AveragingPreferenceInferrer - Class in org.apache.mahout.cf.taste.impl.similarity
Implementations of this interface compute an inferred preference for a user and an item that the user has not expressed any preference for.
AveragingPreferenceInferrer(DataModel) - Constructor for class org.apache.mahout.cf.taste.impl.similarity.AveragingPreferenceInferrer
 
awaitTermination() - Method in class org.apache.mahout.clustering.lda.cvb.TopicModel
 

B

BACKFILL_PERPLEXITY - Static variable in class org.apache.mahout.clustering.lda.cvb.CVB0Driver
 
backwardAlgorithm(HmmModel, int[], boolean) - Static method in class org.apache.mahout.classifier.sequencelearning.hmm.HmmAlgorithms
External function to compute a matrix of beta factors
Bagging - Class in org.apache.mahout.classifier.df
Builds a tree using bagging
Bagging(TreeBuilder, Data) - Constructor for class org.apache.mahout.classifier.df.Bagging
 
bagging(Random) - Method in class org.apache.mahout.classifier.df.data.Data
if data has N cases, sample N cases at random -but with replacement.
bagging(Random, boolean[]) - Method in class org.apache.mahout.classifier.df.data.Data
if data has N cases, sample N cases at random -but with replacement.
BasicStats - Class in org.apache.mahout.math.hadoop.stats
Methods for calculating basic stats (mean, variance, stdDev, etc.) in map/reduce
BASIS_PREFIX - Static variable in class org.apache.mahout.math.hadoop.decomposer.HdfsBackedLanczosState
 
batchTrain(Map<Vector, Vector>, boolean, int) - Method in class org.apache.mahout.clustering.lda.cvb.ModelTrainer
 
BaumWelchTrainer - Class in org.apache.mahout.classifier.sequencelearning.hmm
A class for EM training of HMM from console
BayesAlgorithm - Class in org.apache.mahout.classifier.bayes
Class implementing the Naive Bayes Classifier Algorithm
BayesAlgorithm() - Constructor for class org.apache.mahout.classifier.bayes.BayesAlgorithm
 
BayesClassifierDriver - Class in org.apache.mahout.classifier.bayes.mapreduce.bayes
Create and run the Bayes Classifier
BayesClassifierMapper - Class in org.apache.mahout.classifier.bayes.mapreduce.bayes
Reads the input train set(preprocessed using the BayesFileFormatter).
BayesClassifierMapper() - Constructor for class org.apache.mahout.classifier.bayes.mapreduce.bayes.BayesClassifierMapper
 
BayesClassifierReducer - Class in org.apache.mahout.classifier.bayes.mapreduce.bayes
Can also be used as a local Combiner.
BayesClassifierReducer() - Constructor for class org.apache.mahout.classifier.bayes.mapreduce.bayes.BayesClassifierReducer
 
BayesConstants - Class in org.apache.mahout.classifier.bayes.mapreduce.common
Class containing Constants used by Naive Bayes classifier classes
BayesDriver - Class in org.apache.mahout.classifier.bayes.mapreduce.bayes
Create and run the Bayes Trainer.
BayesDriver() - Constructor for class org.apache.mahout.classifier.bayes.mapreduce.bayes.BayesDriver
 
BayesFeatureCombiner - Class in org.apache.mahout.classifier.bayes.mapreduce.common
Can also be used as a local Combiner.
BayesFeatureCombiner() - Constructor for class org.apache.mahout.classifier.bayes.mapreduce.common.BayesFeatureCombiner
 
BayesFeatureDriver - Class in org.apache.mahout.classifier.bayes.mapreduce.common
Create and run the Bayes Feature Reader Step.
BayesFeatureDriver() - Constructor for class org.apache.mahout.classifier.bayes.mapreduce.common.BayesFeatureDriver
 
BayesFeatureMapper - Class in org.apache.mahout.classifier.bayes.mapreduce.common
Reads the input train set(preprocessed using the BayesFileFormatter).
BayesFeatureMapper() - Constructor for class org.apache.mahout.classifier.bayes.mapreduce.common.BayesFeatureMapper
 
BayesFeatureOutputFormat - Class in org.apache.mahout.classifier.bayes.mapreduce.common
This class extends the MultipleOutputFormat, allowing to write the output data to different output files in sequence file output format.
BayesFeatureOutputFormat() - Constructor for class org.apache.mahout.classifier.bayes.mapreduce.common.BayesFeatureOutputFormat
 
BayesFeatureReducer - Class in org.apache.mahout.classifier.bayes.mapreduce.common
Can also be used as a local Combiner.
BayesFeatureReducer() - Constructor for class org.apache.mahout.classifier.bayes.mapreduce.common.BayesFeatureReducer
 
BayesFileFormatter - Class in org.apache.mahout.classifier
Flatten a file into format that can be read by the Bayes M/R job.
BayesJob - Interface in org.apache.mahout.classifier.bayes.mapreduce.common
Implementors of this interface provide a way for running bayes training jobs on a hadoop cluster.
BayesParameters - Class in org.apache.mahout.classifier.bayes
BayesParameter used for passing parameters to the Map/Reduce Jobs parameters include gramSize,
BayesParameters() - Constructor for class org.apache.mahout.classifier.bayes.BayesParameters
 
BayesParameters(String) - Constructor for class org.apache.mahout.classifier.bayes.BayesParameters
 
BayesTestMapper - Class in org.apache.mahout.classifier.naivebayes.test
Run the input through the model and see if it matches.
BayesTestMapper() - Constructor for class org.apache.mahout.classifier.naivebayes.test.BayesTestMapper
 
BayesTfIdfDriver - Class in org.apache.mahout.classifier.bayes.mapreduce.common
The Driver which drives the Tf-Idf Generation
BayesTfIdfDriver() - Constructor for class org.apache.mahout.classifier.bayes.mapreduce.common.BayesTfIdfDriver
 
BayesTfIdfMapper - Class in org.apache.mahout.classifier.bayes.mapreduce.common
Naive Bayes Tfidf Mapper.
BayesTfIdfMapper() - Constructor for class org.apache.mahout.classifier.bayes.mapreduce.common.BayesTfIdfMapper
 
BayesTfIdfOutputFormat - Class in org.apache.mahout.classifier.bayes.mapreduce.common
This class extends the MultipleOutputFormat, allowing to write the output data to different output files in sequence file output format.
BayesTfIdfOutputFormat() - Constructor for class org.apache.mahout.classifier.bayes.mapreduce.common.BayesTfIdfOutputFormat
 
BayesTfIdfReducer - Class in org.apache.mahout.classifier.bayes.mapreduce.common
Can also be used as a local Combiner beacuse only two values should be there inside the values
BayesTfIdfReducer() - Constructor for class org.apache.mahout.classifier.bayes.mapreduce.common.BayesTfIdfReducer
 
BayesThetaNormalizerDriver - Class in org.apache.mahout.classifier.bayes.mapreduce.bayes
Create and run the Bayes Theta Normalization Step.
BayesThetaNormalizerDriver() - Constructor for class org.apache.mahout.classifier.bayes.mapreduce.bayes.BayesThetaNormalizerDriver
 
BayesThetaNormalizerMapper - Class in org.apache.mahout.classifier.bayes.mapreduce.bayes
Mapper for Calculating the ThetaNormalizer for a label in Naive Bayes Algorithm
BayesThetaNormalizerMapper() - Constructor for class org.apache.mahout.classifier.bayes.mapreduce.bayes.BayesThetaNormalizerMapper
 
BayesThetaNormalizerReducer - Class in org.apache.mahout.classifier.bayes.mapreduce.bayes
Can also be used as a local Combiner beacuse only two values should be there inside the values
BayesThetaNormalizerReducer() - Constructor for class org.apache.mahout.classifier.bayes.mapreduce.bayes.BayesThetaNormalizerReducer
 
BayesUtils - Class in org.apache.mahout.classifier.naivebayes
 
BayesWeightSummerDriver - Class in org.apache.mahout.classifier.bayes.mapreduce.common
Create and run the Bayes Trainer.
BayesWeightSummerDriver() - Constructor for class org.apache.mahout.classifier.bayes.mapreduce.common.BayesWeightSummerDriver
 
BayesWeightSummerMapper - Class in org.apache.mahout.classifier.bayes.mapreduce.common
Calculates weight sum for a unique label, and feature
BayesWeightSummerMapper() - Constructor for class org.apache.mahout.classifier.bayes.mapreduce.common.BayesWeightSummerMapper
 
BayesWeightSummerOutputFormat - Class in org.apache.mahout.classifier.bayes.mapreduce.common
This class extends the MultipleOutputFormat, allowing to write the output data to different output files in sequence file output format.
BayesWeightSummerOutputFormat() - Constructor for class org.apache.mahout.classifier.bayes.mapreduce.common.BayesWeightSummerOutputFormat
 
BayesWeightSummerReducer - Class in org.apache.mahout.classifier.bayes.mapreduce.common
Can also be used as a local Combiner
BayesWeightSummerReducer() - Constructor for class org.apache.mahout.classifier.bayes.mapreduce.common.BayesWeightSummerReducer
 
beta - Variable in class org.apache.mahout.classifier.sgd.AbstractOnlineLogisticRegression
 
BETA - Static variable in interface org.apache.mahout.clustering.spectral.eigencuts.EigencutsKeys
B_0, or the user-specified minimum eigenflow half-life threshold for an eigenvector/eigenvalue pair to be considered.
blockHeight - Variable in class org.apache.mahout.math.hadoop.stochasticsvd.ABtDenseOutJob.QRReducer
 
blockHeight - Variable in class org.apache.mahout.math.hadoop.stochasticsvd.ABtJob.QRReducer
 
blockHeight - Variable in class org.apache.mahout.math.hadoop.stochasticsvd.BtJob.OuterProductCombiner
 
blockHeight - Variable in class org.apache.mahout.math.hadoop.stochasticsvd.BtJob.OuterProductReducer
 
BOOLEAN_DATA - Static variable in class org.apache.mahout.cf.taste.hadoop.item.RecommenderJob
 
BooleanItemPreferenceArray - Class in org.apache.mahout.cf.taste.impl.model
Like BooleanUserPreferenceArray but stores preferences for one item (all item IDs the same) rather than one user.
BooleanItemPreferenceArray(int) - Constructor for class org.apache.mahout.cf.taste.impl.model.BooleanItemPreferenceArray
 
BooleanItemPreferenceArray(List<? extends Preference>, boolean) - Constructor for class org.apache.mahout.cf.taste.impl.model.BooleanItemPreferenceArray
 
BooleanPreference - Class in org.apache.mahout.cf.taste.impl.model
Encapsulates a simple boolean "preference" for an item whose value does not matter (is fixed at 1.0).
BooleanPreference(long, long) - Constructor for class org.apache.mahout.cf.taste.impl.model.BooleanPreference
 
BooleanUserPreferenceArray - Class in org.apache.mahout.cf.taste.impl.model
Like GenericUserPreferenceArray but stores, conceptually, BooleanPreference objects which have no associated preference value.
BooleanUserPreferenceArray(int) - Constructor for class org.apache.mahout.cf.taste.impl.model.BooleanUserPreferenceArray
 
BooleanUserPreferenceArray(List<? extends Preference>) - Constructor for class org.apache.mahout.cf.taste.impl.model.BooleanUserPreferenceArray
 
BOTTOM_LEVEL_CLUSTER_DIRECTORY - Static variable in class org.apache.mahout.clustering.topdown.PathDirectory
 
BtJob - Class in org.apache.mahout.math.hadoop.stochasticsvd
Bt job.
BtJob.BtMapper - Class in org.apache.mahout.math.hadoop.stochasticsvd
 
BtJob.BtMapper() - Constructor for class org.apache.mahout.math.hadoop.stochasticsvd.BtJob.BtMapper
 
BtJob.OuterProductCombiner - Class in org.apache.mahout.math.hadoop.stochasticsvd
 
BtJob.OuterProductCombiner() - Constructor for class org.apache.mahout.math.hadoop.stochasticsvd.BtJob.OuterProductCombiner
 
BtJob.OuterProductReducer - Class in org.apache.mahout.math.hadoop.stochasticsvd
 
BtJob.OuterProductReducer() - Constructor for class org.apache.mahout.math.hadoop.stochasticsvd.BtJob.OuterProductReducer
 
build(Random) - Method in class org.apache.mahout.classifier.df.Bagging
Builds one tree
build(Random, Data) - Method in class org.apache.mahout.classifier.df.builder.DecisionTreeBuilder
 
build(Random, Data) - Method in class org.apache.mahout.classifier.df.builder.DefaultTreeBuilder
 
build(Random, Data) - Method in interface org.apache.mahout.classifier.df.builder.TreeBuilder
Builds a Decision tree using the training data
build(int) - Method in class org.apache.mahout.classifier.df.mapreduce.Builder
 
build(int) - Method in class org.apache.mahout.classifier.df.ref.SequentialBuilder
 
buildClusters(Configuration, Path, Path, DistanceMeasure, double, double, int, boolean) - Static method in class org.apache.mahout.clustering.canopy.CanopyDriver
Convenience method for backwards compatibility
buildClusters(Configuration, Path, Path, DistanceMeasure, double, double, double, double, int, boolean) - Static method in class org.apache.mahout.clustering.canopy.CanopyDriver
Build a directory of Canopy clusters from the input vectors and other arguments.
buildClusters(Configuration, Path, Path, DistributionDescription, int, int, double, boolean) - Static method in class org.apache.mahout.clustering.dirichlet.DirichletDriver
Iterate over the input vectors to produce cluster directories for each iteration
buildClusters(Configuration, Path, Path, Path, DistanceMeasure, double, int, float, boolean) - Static method in class org.apache.mahout.clustering.fuzzykmeans.FuzzyKMeansDriver
Iterate over the input vectors to produce cluster directories for each iteration
buildClusters(Configuration, Path, Path, Path, DistanceMeasure, int, String, boolean) - Static method in class org.apache.mahout.clustering.kmeans.KMeansDriver
Iterate over the input vectors to produce cluster directories for each iteration
buildClusters(Configuration, Path, Path, DistanceMeasure, IKernelProfile, double, double, double, int, boolean, boolean) - Static method in class org.apache.mahout.clustering.meanshift.MeanShiftCanopyDriver
Iterate over the input clusters to produce the next cluster directories for each iteration
buildDataModel(FastByIDMap<PreferenceArray>) - Method in interface org.apache.mahout.cf.taste.eval.DataModelBuilder
Builds a DataModel implementation to be used in an evaluation, given training data.
Builder - Class in org.apache.mahout.classifier.df.mapreduce
Base class for Mapred DecisionForest builders.
Builder(TreeBuilder, Path, Path, Long, Configuration) - Constructor for class org.apache.mahout.classifier.df.mapreduce.Builder
 
buildModel() - Method in class org.apache.mahout.cf.taste.impl.model.file.FileDataModel
 
buildOption(String, String, String, boolean, boolean, String) - Static method in class org.apache.mahout.common.AbstractJob
Build an option with the given parameters.
buildRandom(Configuration, Path, Path, int, DistanceMeasure) - Static method in class org.apache.mahout.clustering.kmeans.RandomSeedGenerator
 
buildRecommender(DataModel) - Method in interface org.apache.mahout.cf.taste.eval.RecommenderBuilder
Builds a Recommender implementation to be evaluated, using the given DataModel.
buildRefreshed(Collection<Refreshable>) - Static method in class org.apache.mahout.cf.taste.impl.common.RefreshHelper
Creates a new and empty Collection if the method parameter is null.
buildTransposeJobConf(Path, Path, int) - Static method in class org.apache.mahout.math.hadoop.TransposeJob
 
buildTransposeJobConf(Configuration, Path, Path, int) - Static method in class org.apache.mahout.math.hadoop.TransposeJob
 
ByScoreLabelResultComparator - Class in org.apache.mahout.classifier.bayes
Compare two results of classification and return the lowest valued one
ByScoreLabelResultComparator() - Constructor for class org.apache.mahout.classifier.bayes.ByScoreLabelResultComparator
 
bytesForString(String) - Static method in class org.apache.mahout.vectorizer.encoders.FeatureVectorEncoder
 
ByValueRecommendedItemComparator - Class in org.apache.mahout.cf.taste.impl.recommender
Defines a natural ordering from most-preferred item (highest value) to least-preferred.
ByValueRecommendedItemComparator() - Constructor for class org.apache.mahout.cf.taste.impl.recommender.ByValueRecommendedItemComparator
 

C

Cache<K,V> - Class in org.apache.mahout.cf.taste.impl.common
An efficient Map-like class which caches values for keys.
Cache(Retriever<? super K, ? extends V>) - Constructor for class org.apache.mahout.cf.taste.impl.common.Cache
Creates a new cache based on the given Retriever.
Cache(Retriever<? super K, ? extends V>, int) - Constructor for class org.apache.mahout.cf.taste.impl.common.Cache
Creates a new cache based on the given Retriever and with given maximum size.
Cache.MatchPredicate<T> - Interface in org.apache.mahout.cf.taste.impl.common
Used by {#link #removeKeysMatching(Object)} to decide things that are matching.
cachedFile(Configuration) - Static method in class org.apache.mahout.common.HadoopUtil
 
cacheFiles(Path, Configuration) - Static method in class org.apache.mahout.common.HadoopUtil
 
CachingContinuousValueEncoder - Class in org.apache.mahout.vectorizer.encoders
 
CachingContinuousValueEncoder(String, int) - Constructor for class org.apache.mahout.vectorizer.encoders.CachingContinuousValueEncoder
 
CachingCVB0Mapper - Class in org.apache.mahout.clustering.lda.cvb
Run ensemble learning via loading the ModelTrainer with two TopicModel instances: one from the previous iteration, the other empty.
CachingCVB0Mapper() - Constructor for class org.apache.mahout.clustering.lda.cvb.CachingCVB0Mapper
 
CachingCVB0PerplexityMapper - Class in org.apache.mahout.clustering.lda.cvb
 
CachingCVB0PerplexityMapper() - Constructor for class org.apache.mahout.clustering.lda.cvb.CachingCVB0PerplexityMapper
 
CachingCVB0PerplexityMapper.Counters - Enum in org.apache.mahout.clustering.lda.cvb
Hadoop counters for CachingCVB0PerplexityMapper, to aid in debugging.
CachingItemSimilarity - Class in org.apache.mahout.cf.taste.impl.similarity
Caches the results from an underlying ItemSimilarity implementation.
CachingItemSimilarity(ItemSimilarity, DataModel) - Constructor for class org.apache.mahout.cf.taste.impl.similarity.CachingItemSimilarity
Creates this on top of the given ItemSimilarity.
CachingItemSimilarity(ItemSimilarity, int) - Constructor for class org.apache.mahout.cf.taste.impl.similarity.CachingItemSimilarity
Creates this on top of the given ItemSimilarity.
CachingRecommender - Class in org.apache.mahout.cf.taste.impl.recommender
A Recommender which caches the results from another Recommender in memory.
CachingRecommender(Recommender) - Constructor for class org.apache.mahout.cf.taste.impl.recommender.CachingRecommender
 
CachingStaticWordValueEncoder - Class in org.apache.mahout.vectorizer.encoders
 
CachingStaticWordValueEncoder(String, int) - Constructor for class org.apache.mahout.vectorizer.encoders.CachingStaticWordValueEncoder
 
CachingTextValueEncoder - Class in org.apache.mahout.vectorizer.encoders
 
CachingTextValueEncoder(String, int) - Constructor for class org.apache.mahout.vectorizer.encoders.CachingTextValueEncoder
 
CachingUserNeighborhood - Class in org.apache.mahout.cf.taste.impl.neighborhood
A caching wrapper around an underlying UserNeighborhood implementation.
CachingUserNeighborhood(UserNeighborhood, DataModel) - Constructor for class org.apache.mahout.cf.taste.impl.neighborhood.CachingUserNeighborhood
 
CachingUserSimilarity - Class in org.apache.mahout.cf.taste.impl.similarity
Caches the results from an underlying UserSimilarity implementation.
CachingUserSimilarity(UserSimilarity, DataModel) - Constructor for class org.apache.mahout.cf.taste.impl.similarity.CachingUserSimilarity
Creates this on top of the given UserSimilarity.
CachingUserSimilarity(UserSimilarity, int) - Constructor for class org.apache.mahout.cf.taste.impl.similarity.CachingUserSimilarity
Creates this on top of the given UserSimilarity.
CachingValueEncoder - Class in org.apache.mahout.vectorizer.encoders
Provides basic hashing semantics for encoders where the probe locations depend only on the name of the variable.
CachingValueEncoder(String, int) - Constructor for class org.apache.mahout.vectorizer.encoders.CachingValueEncoder
 
calculate(int, int, int, int) - Method in class org.apache.mahout.vectorizer.TF
 
calculate(int, int, int, int) - Method in class org.apache.mahout.vectorizer.TFIDF
 
calculate(int, int, int, int) - Method in interface org.apache.mahout.vectorizer.Weight
Experimental
calculateDerivativeValue(double, double) - Method in interface org.apache.mahout.common.kernel.IKernelProfile
 
calculateDerivativeValue(double, double) - Method in class org.apache.mahout.common.kernel.NormalKernelProfile
 
calculateDerivativeValue(double, double) - Method in class org.apache.mahout.common.kernel.TriangularKernelProfile
 
calculateDF(Path, Path, Configuration, int) - Static method in class org.apache.mahout.vectorizer.tfidf.TFIDFConverter
Calculates the document frequencies of all terms from the input set of vectors in SequenceFile format.
CalculateEntropyMapper - Class in org.apache.mahout.math.stats.entropy
Calculates the entropy for the value with H(x) = x * log(x)
CalculateEntropyMapper() - Constructor for class org.apache.mahout.math.stats.entropy.CalculateEntropyMapper
 
CalculateEntropyReducer - Class in org.apache.mahout.math.stats.entropy
Subtracts the partial entropy.
CalculateEntropyReducer() - Constructor for class org.apache.mahout.math.stats.entropy.CalculateEntropyReducer
 
calculatePerplexity(VectorIterable, VectorIterable) - Method in class org.apache.mahout.clustering.lda.cvb.ModelTrainer
 
calculatePerplexity(VectorIterable, VectorIterable, double) - Method in class org.apache.mahout.clustering.lda.cvb.ModelTrainer
 
calculatePerplexity(Vector, Vector, int) - Method in class org.apache.mahout.clustering.lda.cvb.ModelTrainer
 
CalculateSpecificConditionalEntropyMapper - Class in org.apache.mahout.math.stats.entropy
Drops the key.
CalculateSpecificConditionalEntropyMapper() - Constructor for class org.apache.mahout.math.stats.entropy.CalculateSpecificConditionalEntropyMapper
 
calculateValue(double, double) - Method in interface org.apache.mahout.common.kernel.IKernelProfile
 
calculateValue(double, double) - Method in class org.apache.mahout.common.kernel.NormalKernelProfile
 
calculateValue(double, double) - Method in class org.apache.mahout.common.kernel.TriangularKernelProfile
 
call() - Method in class org.apache.mahout.cf.taste.impl.eval.AbstractDifferenceRecommenderEvaluator.PreferenceEstimateCallable
 
CandidateItemsStrategy - Interface in org.apache.mahout.cf.taste.recommender
Used to retrieve all items that could possibly be recommended to the user
Canopy - Class in org.apache.mahout.clustering.canopy
This class models a canopy as a center point, the number of points that are contained within it according to the application of some distance metric, and a point total which is the sum of all the points and is used to compute the centroid when needed.
Canopy() - Constructor for class org.apache.mahout.clustering.canopy.Canopy
Used for deserialization as a writable
Canopy(Vector, int, DistanceMeasure) - Constructor for class org.apache.mahout.clustering.canopy.Canopy
Create a new Canopy containing the given point and canopyId
CANOPY_PATH_KEY - Static variable in interface org.apache.mahout.clustering.canopy.CanopyConfigKeys
 
CanopyClusterer - Class in org.apache.mahout.clustering.canopy
 
CanopyClusterer(DistanceMeasure, double, double) - Constructor for class org.apache.mahout.clustering.canopy.CanopyClusterer
 
CanopyClusterer(Configuration) - Constructor for class org.apache.mahout.clustering.canopy.CanopyClusterer
 
CanopyConfigKeys - Interface in org.apache.mahout.clustering.canopy
 
canopyCovers(Canopy, Vector) - Method in class org.apache.mahout.clustering.canopy.CanopyClusterer
Return if the point is covered by the canopy
canopyCovers(Canopy, Vector) - Method in class org.apache.mahout.clustering.canopy.ClusterMapper
 
CanopyDriver - Class in org.apache.mahout.clustering.canopy
 
CanopyDriver() - Constructor for class org.apache.mahout.clustering.canopy.CanopyDriver
 
CanopyReducer - Class in org.apache.mahout.clustering.canopy
 
CanopyReducer() - Constructor for class org.apache.mahout.clustering.canopy.CanopyReducer
 
capEstimate(float) - Method in class org.apache.mahout.cf.taste.impl.recommender.EstimatedPreferenceCapper
 
CARDINALITY - Static variable in class org.apache.mahout.vectorizer.EncodingMapper
 
CaseAmplification - Class in org.apache.mahout.cf.taste.impl.transforms
Applies "case amplification" to similarities.
CaseAmplification(double) - Constructor for class org.apache.mahout.cf.taste.impl.transforms.CaseAmplification
Creates a transformation based on the given factor.
CategoricalNode - Class in org.apache.mahout.classifier.df.node
 
CategoricalNode() - Constructor for class org.apache.mahout.classifier.df.node.CategoricalNode
 
CategoricalNode(int, double[], Node[]) - Constructor for class org.apache.mahout.classifier.df.node.CategoricalNode
 
CBayesAlgorithm - Class in org.apache.mahout.classifier.bayes
Class implementing the Complementary Naive Bayes Classifier Algorithm
CBayesAlgorithm() - Constructor for class org.apache.mahout.classifier.bayes.CBayesAlgorithm
 
CBayesDriver - Class in org.apache.mahout.classifier.bayes.mapreduce.cbayes
Create and run the Bayes Trainer.
CBayesDriver() - Constructor for class org.apache.mahout.classifier.bayes.mapreduce.cbayes.CBayesDriver
 
CBayesThetaNormalizerDriver - Class in org.apache.mahout.classifier.bayes.mapreduce.cbayes
Create and run the Bayes Trainer.
CBayesThetaNormalizerDriver() - Constructor for class org.apache.mahout.classifier.bayes.mapreduce.cbayes.CBayesThetaNormalizerDriver
 
CBayesThetaNormalizerMapper - Class in org.apache.mahout.classifier.bayes.mapreduce.cbayes
Mapper for Calculating the ThetaNormalizer for a label in Naive Bayes Algorithm
CBayesThetaNormalizerMapper() - Constructor for class org.apache.mahout.classifier.bayes.mapreduce.cbayes.CBayesThetaNormalizerMapper
 
CBayesThetaNormalizerReducer - Class in org.apache.mahout.classifier.bayes.mapreduce.cbayes
Can also be used as a local Combiner beacuse only two values should be there inside the values
CBayesThetaNormalizerReducer() - Constructor for class org.apache.mahout.classifier.bayes.mapreduce.cbayes.CBayesThetaNormalizerReducer
 
CF_KEY - Static variable in interface org.apache.mahout.clustering.canopy.CanopyConfigKeys
 
changeDatum(double) - Method in class org.apache.mahout.cf.taste.impl.common.FixedRunningAverage
 
changeDatum(double) - Method in class org.apache.mahout.cf.taste.impl.common.FullRunningAverage
 
changeDatum(double) - Method in class org.apache.mahout.cf.taste.impl.common.FullRunningAverageAndStdDev
 
changeDatum(double) - Method in class org.apache.mahout.cf.taste.impl.common.InvertedRunningAverage
 
changeDatum(double) - Method in class org.apache.mahout.cf.taste.impl.common.InvertedRunningAverageAndStdDev
 
changeDatum(double) - Method in interface org.apache.mahout.cf.taste.impl.common.RunningAverage
 
changeDatum(double) - Method in class org.apache.mahout.cf.taste.impl.common.WeightedRunningAverage
 
changeDatum(double, double) - Method in class org.apache.mahout.cf.taste.impl.common.WeightedRunningAverage
 
changeDatum(double, double) - Method in class org.apache.mahout.cf.taste.impl.common.WeightedRunningAverageAndStdDev
 
ChebyshevDistanceMeasure - Class in org.apache.mahout.common.distance
This class implements a "Chebyshev distance" metric by finding the maximum difference between each coordinate.
ChebyshevDistanceMeasure() - Constructor for class org.apache.mahout.common.distance.ChebyshevDistanceMeasure
 
checkNotNullAndLog(String, Object) - Static method in class org.apache.mahout.cf.taste.impl.common.jdbc.AbstractJDBCComponent
 
checkNotNullAndLog(String, Object[]) - Static method in class org.apache.mahout.cf.taste.impl.common.jdbc.AbstractJDBCComponent
 
child(int) - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth2.FPTree.FPNode
 
childAtIndex(int, int) - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.FPTree
 
childAtIndex(int, int) - Method in class org.apache.mahout.fpm.pfpgrowth.TransactionTree
 
childCount(int) - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.FPTree
 
childCount() - Method in class org.apache.mahout.fpm.pfpgrowth.TransactionTree
 
childCount(int) - Method in class org.apache.mahout.fpm.pfpgrowth.TransactionTree
 
children() - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth2.FPTree.FPNode
 
childWithAttribute(int, int) - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.FPTree
 
childWithAttribute(int, int) - Method in class org.apache.mahout.fpm.pfpgrowth.TransactionTree
 
CHOOSE_THRESHOLD - Static variable in class org.apache.mahout.cf.taste.impl.eval.GenericRecommenderIRStatsEvaluator
Pass as "relevanceThreshold" argument to GenericRecommenderIRStatsEvaluator.evaluate(RecommenderBuilder, DataModelBuilder, DataModel, IDRescorer, int, double, double) to have it attempt to compute a reasonable threshold.
CIMapper - Class in org.apache.mahout.clustering
 
CIMapper() - Constructor for class org.apache.mahout.clustering.CIMapper
 
CIReducer - Class in org.apache.mahout.clustering
 
CIReducer() - Constructor for class org.apache.mahout.clustering.CIReducer
 
CityBlockSimilarity - Class in org.apache.mahout.cf.taste.impl.similarity
Implementation of City Block distance (also known as Manhattan distance) - the absolute value of the difference of each direction is summed.
CityBlockSimilarity(DataModel) - Constructor for class org.apache.mahout.cf.taste.impl.similarity.CityBlockSimilarity
 
CityBlockSimilarity - Class in org.apache.mahout.math.hadoop.similarity.cooccurrence.measures
 
CityBlockSimilarity() - Constructor for class org.apache.mahout.math.hadoop.similarity.cooccurrence.measures.CityBlockSimilarity
 
Classifier - Class in org.apache.mahout.classifier.df.mapreduce
Mapreduce implementation that classifies the Input data using a previousely built decision forest
Classifier(Path, Path, Path, Path, Configuration) - Constructor for class org.apache.mahout.classifier.df.mapreduce.Classifier
 
Classifier.CMapper - Class in org.apache.mahout.classifier.df.mapreduce
 
Classifier.CMapper() - Constructor for class org.apache.mahout.classifier.df.mapreduce.Classifier.CMapper
 
CLASSIFIER_TUPLE - Static variable in class org.apache.mahout.classifier.bayes.mapreduce.common.BayesConstants
 
ClassifierContext - Class in org.apache.mahout.classifier.bayes
The Classifier Wrapper used for choosing the Algorithm and Datastore
ClassifierContext(Algorithm, Datastore) - Constructor for class org.apache.mahout.classifier.bayes.ClassifierContext
 
ClassifierResult - Class in org.apache.mahout.classifier
Result of a document classification.
ClassifierResult() - Constructor for class org.apache.mahout.classifier.ClassifierResult
 
ClassifierResult(String, double) - Constructor for class org.apache.mahout.classifier.ClassifierResult
 
ClassifierResult(String) - Constructor for class org.apache.mahout.classifier.ClassifierResult
 
ClassifierResult(String, double, double) - Constructor for class org.apache.mahout.classifier.ClassifierResult
 
classify(Vector) - Method in class org.apache.mahout.classifier.AbstractVectorClassifier
Classify a vector returning a vector of numCategories-1 scores.
classify(Matrix) - Method in class org.apache.mahout.classifier.AbstractVectorClassifier
Returns n-1 probabilities, one for each category but the last, for each row of a matrix.
Classify - Class in org.apache.mahout.classifier
Runs the Bayes classifier using the given model location on HDFS
classify(Data, double[]) - Method in class org.apache.mahout.classifier.df.DecisionForest
Classifies the data and calls callback for each classification
classify(Dataset, Random, Instance) - Method in class org.apache.mahout.classifier.df.DecisionForest
predicts the label for the instance
classify(Instance) - Method in class org.apache.mahout.classifier.df.node.CategoricalNode
 
classify(Instance) - Method in class org.apache.mahout.classifier.df.node.Leaf
 
classify(Instance) - Method in class org.apache.mahout.classifier.df.node.Node
predicts the label for the instance
classify(Instance) - Method in class org.apache.mahout.classifier.df.node.NumericalNode
 
classify(Vector) - Method in class org.apache.mahout.classifier.discriminative.LinearModel
Classify a point to either belong to the class modeled by this linear model or not.
classify(Vector) - Method in class org.apache.mahout.classifier.naivebayes.AbstractNaiveBayesClassifier
 
classify(Vector) - Method in class org.apache.mahout.classifier.sgd.AbstractOnlineLogisticRegression
Returns n-1 probabilities, one for each category but the 0-th.
classify(Vector) - Method in class org.apache.mahout.classifier.sgd.CrossFoldLearner
 
classify(Vector) - Method in class org.apache.mahout.classifier.sgd.GradientMachine
 
classify(Vector) - Method in class org.apache.mahout.classifier.sgd.PassiveAggressive
 
classify(Vector) - Method in class org.apache.mahout.clustering.ClusterClassifier
 
classifyDocument(String[], Datastore, String) - Method in interface org.apache.mahout.classifier.bayes.Algorithm
Classify the document and return the Result
classifyDocument(String[], Datastore, String, int) - Method in interface org.apache.mahout.classifier.bayes.Algorithm
Classify the document and return the top numResults
classifyDocument(String[], Datastore, String) - Method in class org.apache.mahout.classifier.bayes.BayesAlgorithm
 
classifyDocument(String[], Datastore, String) - Method in class org.apache.mahout.classifier.bayes.CBayesAlgorithm
 
classifyDocument(String[], String) - Method in class org.apache.mahout.classifier.bayes.ClassifierContext
Classify the document and return the Result
classifyDocument(String[], String, int) - Method in class org.apache.mahout.classifier.bayes.ClassifierContext
Classify the document and return the top numResults
classifyFull(Vector) - Method in class org.apache.mahout.classifier.AbstractVectorClassifier
Returns n probabilities, one for each category.
classifyFull(Vector, Vector) - Method in class org.apache.mahout.classifier.AbstractVectorClassifier
Returns n probabilities, one for each category into a pre-allocated vector.
classifyFull(Matrix) - Method in class org.apache.mahout.classifier.AbstractVectorClassifier
Returns n probabilities, one for each category, for each row of a matrix.
classifyNoLink(Vector) - Method in class org.apache.mahout.classifier.AbstractVectorClassifier
Classify a vector, but don't apply the inverse link function.
classifyNoLink(Vector) - Method in class org.apache.mahout.classifier.sgd.AbstractOnlineLogisticRegression
 
classifyNoLink(Vector) - Method in class org.apache.mahout.classifier.sgd.CrossFoldLearner
 
classifyNoLink(Vector) - Method in class org.apache.mahout.classifier.sgd.GradientMachine
 
classifyNoLink(Vector) - Method in class org.apache.mahout.classifier.sgd.PassiveAggressive
 
classifyParallel(BayesParameters) - Static method in class org.apache.mahout.classifier.bayes.TestClassifier
 
classifyScalar(Vector) - Method in class org.apache.mahout.classifier.AbstractVectorClassifier
Classifies a vector in the special case of a binary classifier where AbstractVectorClassifier.classify(Vector) would return a vector with only one element.
classifyScalar(Matrix) - Method in class org.apache.mahout.classifier.AbstractVectorClassifier
Returns a vector of probabilities of the first category, one for each row of a matrix.
classifyScalar(Vector) - Method in class org.apache.mahout.classifier.naivebayes.AbstractNaiveBayesClassifier
 
classifyScalar(Vector) - Method in class org.apache.mahout.classifier.sgd.AbstractOnlineLogisticRegression
Returns a single scalar probability in the case where we have two categories.
classifyScalar(Vector) - Method in class org.apache.mahout.classifier.sgd.CrossFoldLearner
 
classifyScalar(Vector) - Method in class org.apache.mahout.classifier.sgd.GradientMachine
 
classifyScalar(Vector) - Method in class org.apache.mahout.classifier.sgd.PassiveAggressive
 
classifyScalar(Vector) - Method in class org.apache.mahout.clustering.ClusterClassifier
 
classifyScalarNoLink(Vector) - Method in class org.apache.mahout.classifier.sgd.AbstractOnlineLogisticRegression
 
classifySequential(BayesParameters) - Static method in class org.apache.mahout.classifier.bayes.TestClassifier
 
ClassParameter - Class in org.apache.mahout.common.parameters
 
ClassParameter(String, String, Configuration, Class<?>, String) - Constructor for class org.apache.mahout.common.parameters.ClassParameter
 
ClassUtils - Class in org.apache.mahout.common
 
CLEAN_EIGENVECTORS - Static variable in class org.apache.mahout.math.hadoop.decomposer.EigenVerificationJob
 
cleanup(Mapper<LongWritable, Text, TreeID, MapredOutput>.Context) - Method in class org.apache.mahout.classifier.df.mapreduce.partial.Step1Mapper
 
cleanup(Mapper<IntWritable, VectorWritable, Text, VectorWritable>.Context) - Method in class org.apache.mahout.classifier.naivebayes.training.ThetaMapper
 
cleanup(Mapper<IntWritable, VectorWritable, Text, VectorWritable>.Context) - Method in class org.apache.mahout.classifier.naivebayes.training.WeightsMapper
 
cleanup(Mapper<WritableComparable<?>, VectorWritable, IntWritable, Cluster>.Context) - Method in class org.apache.mahout.clustering.CIMapper
 
cleanup(Mapper<IntWritable, VectorWritable, IntWritable, VectorWritable>.Context) - Method in class org.apache.mahout.clustering.lda.cvb.CachingCVB0Mapper
 
cleanup(Mapper<IntWritable, VectorWritable, DoubleWritable, DoubleWritable>.Context) - Method in class org.apache.mahout.clustering.lda.cvb.CachingCVB0PerplexityMapper
 
cleanup(Mapper<IntWritable, VectorWritable, IntWritable, VectorWritable>.Context) - Method in class org.apache.mahout.clustering.lda.cvb.CVB0DocInferenceMapper
 
cleanup(Mapper<WritableComparable<?>, MeanShiftCanopy, Text, MeanShiftCanopy>.Context) - Method in class org.apache.mahout.clustering.meanshift.MeanShiftCanopyMapper
 
cleanup(Reducer<Text, MeanShiftCanopy, Text, MeanShiftCanopy>.Context) - Method in class org.apache.mahout.clustering.meanshift.MeanShiftCanopyReducer
 
cleanup(Mapper<IntWritable, VectorWritable, IntWritable, VectorWritable>.Context) - Method in class org.apache.mahout.math.hadoop.similarity.cooccurrence.RowSimilarityJob.VectorNormMapper
 
cleanup(Mapper<Writable, VectorWritable, SplitPartitionedWritable, DenseBlockWritable>.Context) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.ABtDenseOutJob.ABtMapper
 
cleanup(Reducer<SplitPartitionedWritable, DenseBlockWritable, SplitPartitionedWritable, VectorWritable>.Context) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.ABtDenseOutJob.QRReducer
 
cleanup(Mapper<Writable, VectorWritable, SplitPartitionedWritable, SparseRowBlockWritable>.Context) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.ABtJob.ABtMapper
 
cleanup(Reducer<SplitPartitionedWritable, SparseRowBlockWritable, SplitPartitionedWritable, VectorWritable>.Context) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.ABtJob.QRReducer
 
cleanup(Mapper<Writable, VectorWritable, LongWritable, SparseRowBlockWritable>.Context) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.BtJob.BtMapper
 
cleanup(Reducer<Writable, SparseRowBlockWritable, Writable, SparseRowBlockWritable>.Context) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.BtJob.OuterProductCombiner
 
cleanup(Reducer<LongWritable, SparseRowBlockWritable, IntWritable, VectorWritable>.Context) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.BtJob.OuterProductReducer
 
cleanup(Mapper<Writable, VectorWritable, SplitPartitionedWritable, VectorWritable>.Context) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.QJob.QMapper
 
cleanup() - Method in class org.apache.mahout.math.hadoop.stochasticsvd.qr.QRFirstStep
 
cleanup(Mapper<Writable, VectorWritable, IntWritable, VectorWritable>.Context) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.YtYJob.YtYMapper
 
cleanup(Reducer<IntWritable, VectorWritable, IntWritable, VectorWritable>.Context) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.YtYJob.YtYReducer
 
clear() - Method in class org.apache.mahout.cf.taste.impl.common.Cache
Clears the cache.
clear() - Method in class org.apache.mahout.cf.taste.impl.common.FastByIDMap
 
clear() - Method in class org.apache.mahout.cf.taste.impl.common.FastIDSet
 
clear() - Method in class org.apache.mahout.cf.taste.impl.common.FastMap
 
clear(long) - Method in class org.apache.mahout.cf.taste.impl.recommender.CachingRecommender
Clears cached recommendations for the given user.
clear() - Method in class org.apache.mahout.cf.taste.impl.recommender.CachingRecommender
Clears all cached recommendations.
clear() - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.FPTree
 
clear() - Method in class org.apache.mahout.math.hadoop.stochasticsvd.SparseRowBlockWritable
 
clearCacheForItem(long) - Method in class org.apache.mahout.cf.taste.impl.similarity.CachingItemSimilarity
 
clearCacheForUser(long) - Method in class org.apache.mahout.cf.taste.impl.similarity.CachingUserSimilarity
 
clearConditional() - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.FPTree
 
clearTempPrefs() - Method in class org.apache.mahout.cf.taste.impl.model.PlusAnonymousUserDataModel
 
clone() - Method in class org.apache.mahout.cf.taste.hadoop.EntityCountWritable
 
clone() - Method in class org.apache.mahout.cf.taste.hadoop.EntityEntityWritable
 
clone() - Method in class org.apache.mahout.cf.taste.hadoop.EntityPrefWritable
 
clone() - Method in class org.apache.mahout.cf.taste.impl.common.FastByIDMap
 
clone() - Method in class org.apache.mahout.cf.taste.impl.common.FastIDSet
 
clone() - Method in class org.apache.mahout.cf.taste.impl.common.FastMap
 
clone() - Method in class org.apache.mahout.cf.taste.impl.model.BooleanItemPreferenceArray
 
clone() - Method in class org.apache.mahout.cf.taste.impl.model.BooleanUserPreferenceArray
 
clone() - Method in class org.apache.mahout.cf.taste.impl.model.GenericItemPreferenceArray
 
clone() - Method in class org.apache.mahout.cf.taste.impl.model.GenericUserPreferenceArray
 
clone() - Method in interface org.apache.mahout.cf.taste.model.PreferenceArray
 
clone() - Method in class org.apache.mahout.classifier.df.data.Data
 
clone() - Method in class org.apache.mahout.classifier.df.mapreduce.MapredOutput
 
clone() - Method in class org.apache.mahout.classifier.df.mapreduce.partial.TreeID
 
clone() - Method in class org.apache.mahout.classifier.sequencelearning.hmm.HmmModel
Get a copy of this model
clone() - Method in class org.apache.mahout.common.IntPairWritable
 
clone() - Method in class org.apache.mahout.math.VarIntWritable
 
clone() - Method in class org.apache.mahout.math.VarLongWritable
 
close() - Method in class org.apache.mahout.classifier.df.mapreduce.inmem.InMemInputFormat.InMemRecordReader
 
close() - Method in interface org.apache.mahout.classifier.OnlineLearner
Prepares the classifier for classification and deallocates any temporary data structures.
close() - Method in class org.apache.mahout.classifier.sgd.AbstractOnlineLogisticRegression
 
close() - Method in class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression
 
close() - Method in class org.apache.mahout.classifier.sgd.CrossFoldLearner
 
close() - Method in class org.apache.mahout.classifier.sgd.GradientMachine
 
close() - Method in class org.apache.mahout.classifier.sgd.PassiveAggressive
 
close() - Method in class org.apache.mahout.clustering.ClusterClassifier
 
close(Collection<? extends Closeable>) - Static method in class org.apache.mahout.common.IOUtils
make sure to close all sources, log all of the problems occurred, clear closeables (to prevent repeating close attempts), re-throw the last one at the end.
close() - Method in class org.apache.mahout.common.IOUtils.DeleteFileOnClose
 
close() - Method in class org.apache.mahout.common.IOUtils.MultipleOutputsCloseableAdapter
 
close() - Method in class org.apache.mahout.common.iterator.FileLineIterator
 
close() - Method in class org.apache.mahout.common.iterator.sequencefile.SequenceFileDirIterator
 
close() - Method in class org.apache.mahout.common.iterator.sequencefile.SequenceFileDirValueIterator
 
close() - Method in class org.apache.mahout.common.iterator.sequencefile.SequenceFileIterator
 
close() - Method in class org.apache.mahout.common.iterator.sequencefile.SequenceFileValueIterator
 
close() - Method in class org.apache.mahout.ep.EvolutionaryProcess
 
close() - Method in class org.apache.mahout.math.hadoop.stochasticsvd.qr.QRFirstStep
 
close() - Method in class org.apache.mahout.math.hadoop.stochasticsvd.qr.QRLastStep
 
close() - Method in class org.apache.mahout.math.hadoop.stochasticsvd.SparseRowBlockAccumulator
 
close() - Method in class org.apache.mahout.math.hadoop.TimesSquaredJob.TimesSquaredMapper
 
closeables - Variable in class org.apache.mahout.math.hadoop.stochasticsvd.BtJob.OuterProductCombiner
 
closeables - Variable in class org.apache.mahout.math.hadoop.stochasticsvd.BtJob.OuterProductReducer
 
closelyBound(MeanShiftCanopy, Vector) - Method in class org.apache.mahout.clustering.meanshift.MeanShiftCanopyClusterer
Return if the point is closely covered by the canopy
Cluster - Interface in org.apache.mahout.clustering
Implementations of this interface have a printable representation and certain attributes that are common across all clustering implementations
cluster(int) - Method in class org.apache.mahout.clustering.dirichlet.DirichletClusterer
Iterate over the sample data, obtaining cluster samples periodically and returning them.
Cluster - Class in org.apache.mahout.clustering.kmeans
 
Cluster() - Constructor for class org.apache.mahout.clustering.kmeans.Cluster
For (de)serialization as a Writable
Cluster(Vector, int, DistanceMeasure) - Constructor for class org.apache.mahout.clustering.kmeans.Cluster
Construct a new cluster with the given point as its center
CLUSTER_CONVERGENCE_KEY - Static variable in interface org.apache.mahout.clustering.fuzzykmeans.FuzzyKMeansConfigKeys
 
CLUSTER_CONVERGENCE_KEY - Static variable in interface org.apache.mahout.clustering.kmeans.KMeansConfigKeys
Configuration key for convergence threshold.
CLUSTER_CONVERGENCE_KEY - Static variable in interface org.apache.mahout.clustering.meanshift.MeanShiftCanopyConfigKeys
 
CLUSTER_FILTER_OPTION - Static variable in class org.apache.mahout.common.commandline.DefaultOptionCreator
 
CLUSTER_PATH_KEY - Static variable in interface org.apache.mahout.clustering.fuzzykmeans.FuzzyKMeansConfigKeys
 
CLUSTER_PATH_KEY - Static variable in interface org.apache.mahout.clustering.kmeans.KMeansConfigKeys
Configuration key for iteration cluster path
CLUSTER_POINTS_KEY - Static variable in interface org.apache.mahout.clustering.meanshift.MeanShiftCanopyConfigKeys
 
ClusterClassifier - Class in org.apache.mahout.clustering
This classifier works with any clustering Cluster.
ClusterClassifier(List<Cluster>) - Constructor for class org.apache.mahout.clustering.ClusterClassifier
The public constructor accepts a list of clusters to become the models
ClusterClassifier() - Constructor for class org.apache.mahout.clustering.ClusterClassifier
 
ClusterCountReader - Class in org.apache.mahout.clustering.topdown.postprocessor
Reads the number of clusters produced by the clustering algorithm.
clusterData(Configuration, Path, Path, Path, DistanceMeasure, double, double, boolean) - Static method in class org.apache.mahout.clustering.canopy.CanopyDriver
 
clusterData(Configuration, Path, Path, Path, boolean, double, boolean) - Static method in class org.apache.mahout.clustering.dirichlet.DirichletDriver
Run the job using supplied arguments
clusterData(Path, Path, Path, DistanceMeasure, double, float, boolean, double, boolean) - Static method in class org.apache.mahout.clustering.fuzzykmeans.FuzzyKMeansDriver
Run the job using supplied arguments
clusterData(Configuration, Path, Path, Path, DistanceMeasure, String, boolean) - Static method in class org.apache.mahout.clustering.kmeans.KMeansDriver
Run the job using supplied arguments
clusterData(Path, Path, Path, boolean) - Static method in class org.apache.mahout.clustering.meanshift.MeanShiftCanopyDriver
Run the job using supplied arguments
CLUSTERED_POINTS_DIR - Static variable in interface org.apache.mahout.clustering.Cluster
 
CLUSTERED_POINTS_DIRECTORY - Static variable in class org.apache.mahout.clustering.topdown.PathDirectory
 
clusterFilterOption() - Static method in class org.apache.mahout.common.commandline.DefaultOptionCreator
 
CLUSTERING_OPTION - Static variable in class org.apache.mahout.common.commandline.DefaultOptionCreator
 
clusteringOption() - Static method in class org.apache.mahout.common.commandline.DefaultOptionCreator
Returns a default command line option for clustering specification.
ClusteringPolicy - Interface in org.apache.mahout.clustering
A ClusteringPolicy captures the semantics of assignment of points to clusters
ClusteringRecommender - Interface in org.apache.mahout.cf.taste.recommender
Interface implemented by "clustering" recommenders.
ClusterIterator - Class in org.apache.mahout.clustering
This is an experimental clustering iterator which works with a ClusteringPolicy and a prior ClusterClassifier which has been initialized with a set of models.
ClusterIterator(ClusteringPolicy) - Constructor for class org.apache.mahout.clustering.ClusterIterator
 
ClusterMapper - Class in org.apache.mahout.clustering.canopy
 
ClusterMapper() - Constructor for class org.apache.mahout.clustering.canopy.ClusterMapper
 
ClusterObservations - Class in org.apache.mahout.clustering
 
ClusterObservations(double, Vector, Vector) - Constructor for class org.apache.mahout.clustering.ClusterObservations
 
ClusterObservations(int, double, Vector, Vector) - Constructor for class org.apache.mahout.clustering.ClusterObservations
 
ClusterObservations() - Constructor for class org.apache.mahout.clustering.ClusterObservations
 
ClusterOutputPostProcessor - Class in org.apache.mahout.clustering.topdown.postprocessor
This class reads the output of any clustering algorithm, and, creates separate directories for different clusters.
ClusterOutputPostProcessor(Path, Path, Configuration) - Constructor for class org.apache.mahout.clustering.topdown.postprocessor.ClusterOutputPostProcessor
 
ClusterOutputPostProcessorDriver - Class in org.apache.mahout.clustering.topdown.postprocessor
Post processes the output of clustering algorithms and groups them into respective clusters.
ClusterOutputPostProcessorMapper - Class in org.apache.mahout.clustering.topdown.postprocessor
Mapper for post processing cluster output.
ClusterOutputPostProcessorMapper() - Constructor for class org.apache.mahout.clustering.topdown.postprocessor.ClusterOutputPostProcessorMapper
 
ClusterOutputPostProcessorReducer - Class in org.apache.mahout.clustering.topdown.postprocessor
Reducer for post processing cluster output.
ClusterOutputPostProcessorReducer() - Constructor for class org.apache.mahout.clustering.topdown.postprocessor.ClusterOutputPostProcessorReducer
 
clusterPoints(List<VectorWritable>, ModelDistribution<VectorWritable>, double, int, int, int, int) - Static method in class org.apache.mahout.clustering.dirichlet.DirichletClusterer
Create a new instance on the sample data with the given additional parameters
clusterPoints(Iterable<Vector>, List<SoftCluster>, DistanceMeasure, double, double, int) - Static method in class org.apache.mahout.clustering.fuzzykmeans.FuzzyKMeansClusterer
This is the reference k-means implementation.
clusterPoints(Iterable<Vector>, List<Cluster>, DistanceMeasure, int, double) - Static method in class org.apache.mahout.clustering.kmeans.KMeansClusterer
This is the reference k-means implementation.
clusterPoints(Iterable<Vector>, DistanceMeasure, IKernelProfile, double, double, double, int) - Static method in class org.apache.mahout.clustering.meanshift.MeanShiftCanopyClusterer
This is the reference mean-shift implementation.
CLUSTERS_DIR - Static variable in interface org.apache.mahout.clustering.Cluster
 
CLUSTERS_IN_OPTION - Static variable in class org.apache.mahout.common.commandline.DefaultOptionCreator
 
ClusterSimilarity - Interface in org.apache.mahout.cf.taste.impl.recommender
Returns the "similarity" between two clusters of users, according to some definition of similarity.
clustersInOption() - Static method in class org.apache.mahout.common.commandline.DefaultOptionCreator
Returns a default command line option for clusters input directory specification.
collapse(String, Analyzer, File, Charset, File) - Static method in class org.apache.mahout.classifier.BayesFileFormatter
Collapse all the files in the inputDir into a single file in the proper Bayes format, 1 document per line
collect(K, V) - Method in class org.apache.mahout.fpm.pfpgrowth.convertors.ContextWriteOutputCollector
 
collect(Integer, List<Pair<List<Integer>, Long>>) - Method in class org.apache.mahout.fpm.pfpgrowth.convertors.integer.IntegerStringOutputConverter
 
collect(K, V) - Method in class org.apache.mahout.fpm.pfpgrowth.convertors.SequenceFileOutputCollector
 
collect(String, List<Pair<List<String>, Long>>) - Method in class org.apache.mahout.fpm.pfpgrowth.convertors.string.StringOutputConverter
 
collect(Integer, FrequentPatternMaxHeap) - Method in class org.apache.mahout.fpm.pfpgrowth.convertors.TopKPatternsOutputConverter
 
collect(Writable, Vector) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.qr.QRFirstStep
 
collect(Long, Vector) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.SparseRowBlockAccumulator
 
CollocCombiner - Class in org.apache.mahout.vectorizer.collocations.llr
Combiner for pass1 of the CollocationDriver.
CollocCombiner() - Constructor for class org.apache.mahout.vectorizer.collocations.llr.CollocCombiner
 
CollocDriver - Class in org.apache.mahout.vectorizer.collocations.llr
Driver for LLR Collocation discovery mapreduce job
CollocDriver() - Constructor for class org.apache.mahout.vectorizer.collocations.llr.CollocDriver
 
CollocMapper - Class in org.apache.mahout.vectorizer.collocations.llr
Pass 1 of the Collocation discovery job which generated ngrams and emits ngrams an their component n-1grams.
CollocMapper() - Constructor for class org.apache.mahout.vectorizer.collocations.llr.CollocMapper
 
CollocMapper.Count - Enum in org.apache.mahout.vectorizer.collocations.llr
 
CollocReducer - Class in org.apache.mahout.vectorizer.collocations.llr
Reducer for Pass 1 of the collocation identification job.
CollocReducer() - Constructor for class org.apache.mahout.vectorizer.collocations.llr.CollocReducer
 
CollocReducer.Skipped - Enum in org.apache.mahout.vectorizer.collocations.llr
 
CommandLineUtil - Class in org.apache.mahout.common
 
compare(RecommendedItem, RecommendedItem) - Method in class org.apache.mahout.cf.taste.impl.recommender.ByValueRecommendedItemComparator
 
compare(ClassifierResult, ClassifierResult) - Method in class org.apache.mahout.classifier.bayes.ByScoreLabelResultComparator
 
compare(WritableComparable, WritableComparable) - Method in class org.apache.mahout.classifier.bayes.mapreduce.common.FeatureLabelComparator
 
compare(byte[], int, int, byte[], int, int) - Method in class org.apache.mahout.common.IntPairWritable.Comparator
 
compare(byte[], int, int, byte[], int, int) - Method in class org.apache.mahout.common.IntPairWritable.FirstGroupingComparator
 
compare(Object, Object) - Method in class org.apache.mahout.common.IntPairWritable.FirstGroupingComparator
 
compare(Pair<A, B>, Pair<A, B>) - Method in class org.apache.mahout.fpm.pfpgrowth.CountDescendingPairComparator
 
compare(Object, Object) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.SplitPartitionedWritable.SplitGroupingComparator
 
COMPARE_BY_SCORE_AND_LABEL - Static variable in class org.apache.mahout.classifier.ClassifierResult
 
compareTo(EntityEntityWritable) - Method in class org.apache.mahout.cf.taste.hadoop.EntityEntityWritable
 
compareTo(SimilarUser) - Method in class org.apache.mahout.cf.taste.impl.recommender.SimilarUser
Defines an ordering from most similar to least similar.
compareTo(GenericItemSimilarity.ItemItemSimilarity) - Method in class org.apache.mahout.cf.taste.impl.similarity.GenericItemSimilarity.ItemItemSimilarity
Defines an ordering from highest similarity to lowest.
compareTo(GenericUserSimilarity.UserUserSimilarity) - Method in class org.apache.mahout.cf.taste.impl.similarity.GenericUserSimilarity.UserUserSimilarity
Defines an ordering from highest similarity to lowest.
compareTo(ModelDissector.Weight) - Method in class org.apache.mahout.classifier.sgd.ModelDissector.Weight
 
compareTo(IntegerTuple) - Method in class org.apache.mahout.common.IntegerTuple
 
compareTo(BinaryComparable) - Method in class org.apache.mahout.common.IntPairWritable
 
compareTo(IntPairWritable.Frequency) - Method in class org.apache.mahout.common.IntPairWritable.Frequency
 
compareTo(IntTuple) - Method in class org.apache.mahout.common.IntTuple
 
compareTo(LongPair) - Method in class org.apache.mahout.common.LongPair
 
compareTo(Pair<A, B>) - Method in class org.apache.mahout.common.Pair
Defines an ordering on pairs that sorts by first value's natural ordering, ascending, and then by second value's natural ordering.
compareTo(StringTuple) - Method in class org.apache.mahout.common.StringTuple
 
compareTo(State<T, U>) - Method in class org.apache.mahout.ep.State
Natural order is to sort in descending order of score.
compareTo(Pattern) - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.Pattern
 
compareTo(DistributedRowMatrix.MatrixEntryWritable) - Method in class org.apache.mahout.math.hadoop.DistributedRowMatrix.MatrixEntryWritable
 
compareTo(SplitPartitionedWritable) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.SplitPartitionedWritable
 
compareTo(VarIntWritable) - Method in class org.apache.mahout.math.VarIntWritable
 
compareTo(VarLongWritable) - Method in class org.apache.mahout.math.VarLongWritable
 
COMPLEMENTARY - Static variable in class org.apache.mahout.classifier.naivebayes.test.TestNaiveBayesDriver
 
ComplementaryNaiveBayesClassifier - Class in org.apache.mahout.classifier.naivebayes
Class implementing the Naive Bayes Classifier Algorithm
ComplementaryNaiveBayesClassifier(NaiveBayesModel) - Constructor for class org.apache.mahout.classifier.naivebayes.ComplementaryNaiveBayesClassifier
 
ComplementaryThetaTrainer - Class in org.apache.mahout.classifier.naivebayes.training
 
ComplementaryThetaTrainer(Vector, Vector, double) - Constructor for class org.apache.mahout.classifier.naivebayes.training.ComplementaryThetaTrainer
 
CompositeParameter<T extends Parametered> - Class in org.apache.mahout.common.parameters
A placeholder for some sort of class with more parameters.
CompositeParameter(Class<T>, String, String, Configuration, T, String) - Constructor for class org.apache.mahout.common.parameters.CompositeParameter
 
compute() - Method in interface org.apache.mahout.clustering.GaussianAccumulator
Compute the mean, variance and standard deviation
compute() - Method in class org.apache.mahout.clustering.OnlineGaussianAccumulator
 
compute() - Method in class org.apache.mahout.clustering.RunningSumsGaussianAccumulator
 
computeCentroid() - Method in class org.apache.mahout.clustering.AbstractCluster
Compute the centroid by averaging the pointTotals
computeConvergence(Cluster) - Method in class org.apache.mahout.clustering.fuzzykmeans.FuzzyKMeansClusterer
Return if the cluster is converged by comparing its center and centroid.
computeConvergence(DistanceMeasure, double) - Method in class org.apache.mahout.clustering.kmeans.Cluster
Return if the cluster is converged by comparing its center and centroid.
computeConvergence(Cluster, double) - Method in class org.apache.mahout.clustering.kmeans.KMeansClusterer
 
computeFinalEvaluation() - Method in class org.apache.mahout.cf.taste.impl.eval.AbstractDifferenceRecommenderEvaluator
 
computeFinalEvaluation() - Method in class org.apache.mahout.cf.taste.impl.eval.AverageAbsoluteDifferenceRecommenderEvaluator
 
computeFinalEvaluation() - Method in class org.apache.mahout.cf.taste.impl.eval.RMSRecommenderEvaluator
 
computeMean() - Method in class org.apache.mahout.math.hadoop.stats.VarianceTotals
 
computeNext() - Method in class org.apache.mahout.common.iterator.CountingIterator
 
computeNext() - Method in class org.apache.mahout.common.iterator.FileLineIterator
 
computeNext() - Method in class org.apache.mahout.common.iterator.SamplingIterator
 
computeNext() - Method in class org.apache.mahout.common.iterator.sequencefile.SequenceFileIterator
 
computeNext() - Method in class org.apache.mahout.common.iterator.sequencefile.SequenceFileValueIterator
 
computeNext() - Method in class org.apache.mahout.common.lucene.TokenStreamIterator
 
computeNext() - Method in class org.apache.mahout.fpm.pfpgrowth.MultiTransactionTreeIterator
 
computeParameters() - Method in class org.apache.mahout.clustering.AbstractCluster
 
computeParameters() - Method in class org.apache.mahout.clustering.dirichlet.DirichletCluster
 
computeParameters() - Method in interface org.apache.mahout.clustering.Model
Compute a new set of posterior parameters based upon the Observations that have been observed since my creation
computePi(Collection<SoftCluster>, List<Double>) - Method in class org.apache.mahout.clustering.fuzzykmeans.FuzzyKMeansClusterer
 
computeProbWeight(double, Iterable<Double>) - Method in class org.apache.mahout.clustering.fuzzykmeans.FuzzyKMeansClusterer
Computes the probability of a point belonging to a cluster
computeQtHat(double[][], int, Iterator<UpperTriangular>) - Static method in class org.apache.mahout.math.hadoop.stochasticsvd.qr.GivensThinSolver
 
computeRmse(Path) - Method in class org.apache.mahout.cf.taste.hadoop.als.FactorizationEvaluator
 
computeSplit(Data, int) - Method in class org.apache.mahout.classifier.df.split.DefaultIgSplit
 
computeSplit(Data, int) - Method in class org.apache.mahout.classifier.df.split.IgSplit
Computes the best split for the given attribute
computeSplit(Data, int) - Method in class org.apache.mahout.classifier.df.split.OptIgSplit
 
computeSplit(Data, int) - Method in class org.apache.mahout.classifier.df.split.RegressionSplit
 
computeU(Iterable<File>, File) - Method in class org.apache.mahout.math.ssvd.SequentialOutOfCoreSvd
 
computeV(File, int) - Method in class org.apache.mahout.math.ssvd.SequentialOutOfCoreSvd
 
computeVariance() - Method in class org.apache.mahout.math.hadoop.stats.VarianceTotals
 
computeVarianceForGivenMean(double) - Method in class org.apache.mahout.math.hadoop.stats.VarianceTotals
 
computeYRow(Vector, double[]) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.Omega
Deprecated. 
computeYRow(Vector, Vector) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.Omega
A version to compute yRow as a sparse vector in case of extremely sparse matrices
Condition - Class in org.apache.mahout.classifier.df.data.conditions
Condition on Instance
Condition() - Constructor for class org.apache.mahout.classifier.df.data.conditions.Condition
 
conditional(int) - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.FPTree
 
ConditionalEntropy - Class in org.apache.mahout.math.stats.entropy
A Hadoop job to compute the conditional entropy H(Value|Key) for a sequence file.
ConditionalEntropy() - Constructor for class org.apache.mahout.math.stats.entropy.ConditionalEntropy
 
conf(Parametered) - Static method in class org.apache.mahout.common.parameters.Parametered.ParameteredGeneralizations
 
config(DistanceMeasure, double, double) - Method in class org.apache.mahout.clustering.canopy.CanopyClusterer
Configure the Canopy for unit tests
configure(JobConf) - Method in class org.apache.mahout.classifier.bayes.mapreduce.bayes.BayesClassifierMapper
 
configure(JobConf) - Method in class org.apache.mahout.classifier.bayes.mapreduce.bayes.BayesThetaNormalizerMapper
 
configure(JobConf) - Method in class org.apache.mahout.classifier.bayes.mapreduce.cbayes.CBayesThetaNormalizerMapper
 
configure(JobConf) - Method in class org.apache.mahout.classifier.bayes.mapreduce.common.BayesFeatureMapper
 
configure(JobConf) - Method in class org.apache.mahout.classifier.bayes.mapreduce.common.BayesFeatureReducer
 
configure(JobConf) - Method in class org.apache.mahout.classifier.bayes.mapreduce.common.BayesTfIdfMapper
 
configure(JobConf) - Method in class org.apache.mahout.classifier.bayes.mapreduce.common.FeaturePartitioner
 
configure(boolean, TreeBuilder, Dataset) - Method in class org.apache.mahout.classifier.df.mapreduce.MapredMapper
Useful for testing
configure(Long, int, int, int) - Method in class org.apache.mahout.classifier.df.mapreduce.partial.Step1Mapper
Useful when testing
configure(Configuration) - Method in class org.apache.mahout.clustering.AbstractCluster
 
configure(Configuration) - Method in class org.apache.mahout.clustering.canopy.CanopyClusterer
Configure the Canopy and its distance measure
configure(Configuration) - Method in class org.apache.mahout.clustering.dirichlet.DirichletCluster
 
configure(Configuration) - Method in class org.apache.mahout.clustering.DistanceMeasureCluster
 
configure(LDAState) - Method in class org.apache.mahout.clustering.lda.LDADocumentTopicMapper
 
configure(Configuration) - Method in class org.apache.mahout.clustering.lda.LDADocumentTopicMapper
 
configure(LDAState) - Method in class org.apache.mahout.clustering.lda.LDAWordTopicMapper
 
configure(Configuration) - Method in class org.apache.mahout.clustering.lda.LDAWordTopicMapper
 
configure(Configuration) - Method in class org.apache.mahout.common.distance.ChebyshevDistanceMeasure
 
configure(Configuration) - Method in class org.apache.mahout.common.distance.CosineDistanceMeasure
 
configure(Configuration) - Method in class org.apache.mahout.common.distance.MahalanobisDistanceMeasure
 
configure(Configuration) - Method in class org.apache.mahout.common.distance.ManhattanDistanceMeasure
 
configure(Configuration) - Method in class org.apache.mahout.common.distance.MinkowskiDistanceMeasure
 
configure(Configuration) - Method in class org.apache.mahout.common.distance.SquaredEuclideanDistanceMeasure
 
configure(Configuration) - Method in class org.apache.mahout.common.distance.WeightedDistanceMeasure
 
configure(Configuration) - Method in class org.apache.mahout.common.parameters.AbstractParameter
 
configure(Configuration) - Method in class org.apache.mahout.common.parameters.CompositeParameter
 
configure(Configuration) - Method in interface org.apache.mahout.common.parameters.Parametered
 
configure(JobConf) - Method in class org.apache.mahout.math.hadoop.MatrixMultiplicationJob.MatrixMultiplyMapper
 
configure(JobConf) - Method in class org.apache.mahout.math.hadoop.TimesSquaredJob.TimesSquaredMapper
 
configure(JobConf) - Method in class org.apache.mahout.math.hadoop.TimesSquaredJob.VectorSummingReducer
 
configure(JobConf) - Method in class org.apache.mahout.math.hadoop.TransposeJob.TransposeMapper
 
configureJob(Job) - Method in class org.apache.mahout.classifier.df.mapreduce.Builder
Used by the inheriting classes to configure the job
configureJob(Job) - Method in class org.apache.mahout.classifier.df.mapreduce.inmem.InMemBuilder
 
configureJob(Job) - Method in class org.apache.mahout.classifier.df.mapreduce.partial.PartialBuilder
 
configureParameters(Parametered, Configuration) - Static method in class org.apache.mahout.common.parameters.Parametered.ParameteredGeneralizations
 
configureParameters(String, Parametered, Configuration) - Static method in class org.apache.mahout.common.parameters.Parametered.ParameteredGeneralizations
Calls Parametered.createParameters(String,org.apache.hadoop.conf.Configuration) on parameter parmetered, and then recur down its composite tree to invoke Parametered.createParameters(String,org.apache.hadoop.conf.Configuration) and Parametered.configure(org.apache.hadoop.conf.Configuration) on each composite part.
confusion() - Method in class org.apache.mahout.classifier.evaluation.Auc
Returns the confusion matrix for the classifier supposing that we were to use a particular threshold.
ConfusionMatrix - Class in org.apache.mahout.classifier
The ConfusionMatrix Class stores the result of Classification of a Test Dataset.
ConfusionMatrix(Collection<String>, String) - Constructor for class org.apache.mahout.classifier.ConfusionMatrix
 
ConfusionMatrix(Matrix) - Constructor for class org.apache.mahout.classifier.ConfusionMatrix
 
confusionMatrixSeqFileExport(Parameters, ConfusionMatrix) - Static method in class org.apache.mahout.classifier.bayes.mapreduce.bayes.BayesClassifierDriver
 
ConjugateGradientOptimizer - Class in org.apache.mahout.cf.taste.impl.recommender.knn
 
ConjugateGradientOptimizer() - Constructor for class org.apache.mahout.cf.taste.impl.recommender.knn.ConjugateGradientOptimizer
 
consider(int, int, double, double, double) - Method in class org.apache.mahout.math.hadoop.similarity.cooccurrence.measures.CooccurrenceCountSimilarity
 
consider(int, int, double, double, double) - Method in class org.apache.mahout.math.hadoop.similarity.cooccurrence.measures.CosineSimilarity
 
consider(int, int, double, double, double) - Method in class org.apache.mahout.math.hadoop.similarity.cooccurrence.measures.CountbasedMeasure
 
consider(int, int, double, double, double) - Method in class org.apache.mahout.math.hadoop.similarity.cooccurrence.measures.EuclideanDistanceSimilarity
 
consider(int, int, double, double, double) - Method in class org.apache.mahout.math.hadoop.similarity.cooccurrence.measures.TanimotoCoefficientSimilarity
 
consider(int, int, double, double, double) - Method in interface org.apache.mahout.math.hadoop.similarity.cooccurrence.measures.VectorSimilarityMeasure
 
ConstantValueEncoder - Class in org.apache.mahout.vectorizer.encoders
An encoder that does the standard thing for a virtual bias term.
ConstantValueEncoder(String) - Constructor for class org.apache.mahout.vectorizer.encoders.ConstantValueEncoder
 
contains(long) - Method in class org.apache.mahout.cf.taste.impl.common.FastIDSet
 
contains(Instance) - Method in class org.apache.mahout.classifier.df.data.Data
 
contains(K) - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.LeastKCache
 
containsKey(long) - Method in class org.apache.mahout.cf.taste.impl.common.FastByIDMap
 
containsKey(Object) - Method in class org.apache.mahout.cf.taste.impl.common.FastMap
 
containsValue(Object) - Method in class org.apache.mahout.cf.taste.impl.common.FastByIDMap
 
containsValue(Object) - Method in class org.apache.mahout.cf.taste.impl.common.FastMap
 
ContextStatusUpdater<IK extends org.apache.hadoop.io.Writable,IV extends org.apache.hadoop.io.Writable,K extends org.apache.hadoop.io.Writable,V extends org.apache.hadoop.io.Writable> - Class in org.apache.mahout.fpm.pfpgrowth.convertors
Updates the Context object of a Reducer class
ContextStatusUpdater(Reducer<IK, IV, K, V>.Context) - Constructor for class org.apache.mahout.fpm.pfpgrowth.convertors.ContextStatusUpdater
 
ContextWriteOutputCollector<IK extends org.apache.hadoop.io.Writable,IV extends org.apache.hadoop.io.Writable,K extends org.apache.hadoop.io.Writable,V extends org.apache.hadoop.io.Writable> - Class in org.apache.mahout.fpm.pfpgrowth.convertors
An output collector for Reducer for PFPGrowth which updates the status as well as writes the patterns generated by the algorithm
ContextWriteOutputCollector(Reducer<IK, IV, K, V>.Context) - Constructor for class org.apache.mahout.fpm.pfpgrowth.convertors.ContextWriteOutputCollector
 
CONTINUOUS_VALUE_HASH_SEED - Static variable in class org.apache.mahout.vectorizer.encoders.FeatureVectorEncoder
 
ContinuousValueEncoder - Class in org.apache.mahout.vectorizer.encoders
Continuous values are stored in fixed randomized location in the feature vector.
ContinuousValueEncoder(String) - Constructor for class org.apache.mahout.vectorizer.encoders.ContinuousValueEncoder
 
CONTROL_PATH_KEY - Static variable in interface org.apache.mahout.clustering.meanshift.MeanShiftCanopyConfigKeys
 
CONVERGENCE_DELTA_OPTION - Static variable in class org.apache.mahout.common.commandline.DefaultOptionCreator
 
convergenceOption() - Static method in class org.apache.mahout.common.commandline.DefaultOptionCreator
Returns a default command line option for convergence delta specification.
convert(CharSequence) - Method in class org.apache.mahout.classifier.df.data.DataConverter
 
CooccurrenceCountSimilarity - Class in org.apache.mahout.math.hadoop.similarity.cooccurrence.measures
 
CooccurrenceCountSimilarity() - Constructor for class org.apache.mahout.math.hadoop.similarity.cooccurrence.measures.CooccurrenceCountSimilarity
 
copy() - Method in class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression.Wrapper
 
copy() - Method in class org.apache.mahout.classifier.sgd.CrossFoldLearner
 
copy() - Method in class org.apache.mahout.classifier.sgd.GradientMachine
 
copy() - Method in class org.apache.mahout.classifier.sgd.OnlineLogisticRegression
 
copy() - Method in class org.apache.mahout.classifier.sgd.PassiveAggressive
 
copy() - Method in interface org.apache.mahout.ep.Payload
 
copy() - Method in class org.apache.mahout.ep.State
Deep copies a state, useful in mutation.
CopyConstructorIterator<T> - Class in org.apache.mahout.common.iterator
An iterator that copies the values in an underlying iterator by finding an appropriate copy constructor.
CopyConstructorIterator(Iterator<? extends T>) - Constructor for class org.apache.mahout.common.iterator.CopyConstructorIterator
 
copyFrom(AbstractOnlineLogisticRegression) - Method in class org.apache.mahout.classifier.sgd.AbstractOnlineLogisticRegression
 
copyFrom(GradientMachine) - Method in class org.apache.mahout.classifier.sgd.GradientMachine
 
copyFrom(OnlineLogisticRegression) - Method in class org.apache.mahout.classifier.sgd.OnlineLogisticRegression
 
copyFrom(PassiveAggressive) - Method in class org.apache.mahout.classifier.sgd.PassiveAggressive
 
CosineDistanceMeasure - Class in org.apache.mahout.common.distance
This class implements a cosine distance metric by dividing the dot product of two vectors by the product of their lengths
CosineDistanceMeasure() - Constructor for class org.apache.mahout.common.distance.CosineDistanceMeasure
 
CosineSimilarity - Class in org.apache.mahout.math.hadoop.similarity.cooccurrence.measures
 
CosineSimilarity() - Constructor for class org.apache.mahout.math.hadoop.similarity.cooccurrence.measures.CosineSimilarity
 
count() - Method in class org.apache.mahout.clustering.AbstractCluster
 
count() - Method in class org.apache.mahout.clustering.dirichlet.DirichletCluster
 
count() - Method in interface org.apache.mahout.clustering.Model
Return the number of observations that have been observed by this model
count(int) - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.FPTree
 
count() - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.FrequentPatternMaxHeap
 
count() - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth2.FPTree.FPNode
 
count(int) - Method in class org.apache.mahout.fpm.pfpgrowth.TransactionTree
 
CountbasedMeasure - Class in org.apache.mahout.math.hadoop.similarity.cooccurrence.measures
 
CountbasedMeasure() - Constructor for class org.apache.mahout.math.hadoop.similarity.cooccurrence.measures.CountbasedMeasure
 
CountDescendingPairComparator<A extends Comparable<? super A>,B extends Comparable<? super B>> - Class in org.apache.mahout.fpm.pfpgrowth
Defines an ordering on Pairs whose second element is a count.
CountDescendingPairComparator() - Constructor for class org.apache.mahout.fpm.pfpgrowth.CountDescendingPairComparator
 
CountingIterator - Class in org.apache.mahout.common.iterator
Iterates over the integers from 0 through to-1.
CountingIterator(int) - Constructor for class org.apache.mahout.common.iterator.CountingIterator
 
countLabels(int[]) - Method in class org.apache.mahout.classifier.df.data.Data
Counts the number of occurrences of each label value
This method can be used when the criterion variable is the categorical attribute.
countRecords(Path, Configuration) - Static method in class org.apache.mahout.common.HadoopUtil
 
countRecords(Path, PathType, PathFilter, Configuration) - Static method in class org.apache.mahout.common.HadoopUtil
Count all the records in a directory using a SequenceFileDirValueIterator
createCanopies(List<Vector>, DistanceMeasure, double, double) - Static method in class org.apache.mahout.clustering.canopy.CanopyClusterer
Iterate through the points, adding new canopies.
createCanopyFromVectors(Configuration, Path, Path, DistanceMeasure, boolean) - Static method in class org.apache.mahout.clustering.meanshift.MeanShiftCanopyDriver
Convert input vectors to MeanShiftCanopies for further processing
createConditionalNode(int, long) - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.FPTree
 
createDampingVector(int, double) - Method in class org.apache.mahout.graph.linkanalysis.PageRankJob
 
createDampingVector(int, double) - Method in class org.apache.mahout.graph.linkanalysis.RandomWalkWithRestartJob
 
createFactorization(double[][], double[][]) - Method in class org.apache.mahout.cf.taste.impl.recommender.svd.AbstractFactorizer
 
createHashFunctions(HashFactory.HashType, int) - Static method in class org.apache.mahout.clustering.minhash.HashFactory
 
createMatrixMultiplyJobConf(Path, Path, Path, int) - Static method in class org.apache.mahout.math.hadoop.MatrixMultiplicationJob
 
createMatrixMultiplyJobConf(Configuration, Path, Path, Path, int) - Static method in class org.apache.mahout.math.hadoop.MatrixMultiplicationJob
 
createModelDistribution() - Method in class org.apache.mahout.clustering.dirichlet.models.DistributionDescription
Create an instance of AbstractVectorModelDistribution from the given command line arguments
createMoreFreqConditionalTree(int) - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth2.FPTree
Returns a conditional FP tree based on the targetAttr, containing only items that are more frequent.
createNode(int, int, long) - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.FPTree
 
createParameters(String, Configuration) - Method in class org.apache.mahout.clustering.AbstractCluster
 
createParameters(String, Configuration) - Method in class org.apache.mahout.clustering.dirichlet.DirichletCluster
 
createParameters(String, Configuration) - Method in class org.apache.mahout.common.distance.ChebyshevDistanceMeasure
 
createParameters(String, Configuration) - Method in class org.apache.mahout.common.distance.CosineDistanceMeasure
 
createParameters(String, Configuration) - Method in class org.apache.mahout.common.distance.MahalanobisDistanceMeasure
 
createParameters(String, Configuration) - Method in class org.apache.mahout.common.distance.ManhattanDistanceMeasure
 
createParameters(String, Configuration) - Method in class org.apache.mahout.common.distance.MinkowskiDistanceMeasure
 
createParameters(String, Configuration) - Method in class org.apache.mahout.common.distance.SquaredEuclideanDistanceMeasure
 
createParameters(String, Configuration) - Method in class org.apache.mahout.common.distance.WeightedDistanceMeasure
 
createParameters(String, Configuration) - Method in class org.apache.mahout.common.parameters.AbstractParameter
 
createParameters(String, Configuration) - Method in class org.apache.mahout.common.parameters.CompositeParameter
 
createParameters(String, Configuration) - Method in interface org.apache.mahout.common.parameters.Parametered
EXPERT: consumers should never have to call this method.
createQueue() - Method in class org.apache.mahout.cf.taste.impl.recommender.svd.ALSWRFactorizer
 
createRecordReader(InputSplit, TaskAttemptContext) - Method in class org.apache.mahout.classifier.df.mapreduce.inmem.InMemInputFormat
 
createRootNode() - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.FPTree
 
createScoringVector() - Method in class org.apache.mahout.classifier.naivebayes.NaiveBayesModel
 
createState(Configuration) - Static method in class org.apache.mahout.clustering.lda.LDADriver
 
createState(Configuration, boolean) - Static method in class org.apache.mahout.clustering.lda.LDADriver
 
createTermFrequencyVectors(Path, Path, String, Configuration, int, int, float, float, boolean, int, int, boolean, boolean) - Static method in class org.apache.mahout.vectorizer.DictionaryVectorizer
Create Term Frequency (Tf) Vectors from the input set of documents in SequenceFile format.
createTimesJobConf(Vector, int, Path, Path) - Static method in class org.apache.mahout.math.hadoop.TimesSquaredJob
 
createTimesJobConf(Configuration, Vector, int, Path, Path) - Static method in class org.apache.mahout.math.hadoop.TimesSquaredJob
 
createTimesSquaredJobConf(Vector, Path, Path) - Static method in class org.apache.mahout.math.hadoop.TimesSquaredJob
 
createTimesSquaredJobConf(Configuration, Vector, Path, Path) - Static method in class org.apache.mahout.math.hadoop.TimesSquaredJob
 
createTimesSquaredJobConf(Vector, Path, Path, Class<? extends TimesSquaredJob.TimesSquaredMapper>, Class<? extends TimesSquaredJob.VectorSummingReducer>) - Static method in class org.apache.mahout.math.hadoop.TimesSquaredJob
 
createTimesSquaredJobConf(Configuration, Vector, Path, Path, Class<? extends TimesSquaredJob.TimesSquaredMapper>, Class<? extends TimesSquaredJob.VectorSummingReducer>) - Static method in class org.apache.mahout.math.hadoop.TimesSquaredJob
 
createTimesSquaredJobConf(Vector, int, Path, Path, Class<? extends TimesSquaredJob.TimesSquaredMapper>, Class<? extends TimesSquaredJob.VectorSummingReducer>) - Static method in class org.apache.mahout.math.hadoop.TimesSquaredJob
 
createTimesSquaredJobConf(Configuration, Vector, int, Path, Path, Class<? extends TimesSquaredJob.TimesSquaredMapper>, Class<? extends TimesSquaredJob.VectorSummingReducer>) - Static method in class org.apache.mahout.math.hadoop.TimesSquaredJob
 
createVectors(Path, Path, VectorizerConfig) - Method in class org.apache.mahout.vectorizer.DictionaryVectorizer
 
createVectors(Path, Path, VectorizerConfig) - Method in class org.apache.mahout.vectorizer.SimpleTextEncodingVectorizer
 
createVectors(Path, Path, VectorizerConfig) - Method in interface org.apache.mahout.vectorizer.Vectorizer
 
CrossFoldLearner - Class in org.apache.mahout.classifier.sgd
Does cross-fold validation of log-likelihood and AUC on several online logistic regression models.
CrossFoldLearner() - Constructor for class org.apache.mahout.classifier.sgd.CrossFoldLearner
 
CrossFoldLearner(int, int, int, PriorFunction) - Constructor for class org.apache.mahout.classifier.sgd.CrossFoldLearner
 
CsvRecordFactory - Class in org.apache.mahout.classifier.sgd
Converts csv data lines to vectors.
CsvRecordFactory(String, Map<String, String>) - Constructor for class org.apache.mahout.classifier.sgd.CsvRecordFactory
Construct a parser for CSV lines that encodes the parsed data in vector form.
CsvRecordFactory(String, String, Map<String, String>) - Constructor for class org.apache.mahout.classifier.sgd.CsvRecordFactory
 
currentLearningRate() - Method in class org.apache.mahout.classifier.sgd.AbstractOnlineLogisticRegression
 
currentLearningRate() - Method in class org.apache.mahout.classifier.sgd.OnlineLogisticRegression
 
CUTMATRIX_PATH - Static variable in interface org.apache.mahout.clustering.spectral.eigencuts.EigencutsKeys
Refers to the Path to the SequenceFile representing the cut matrix
CVB0DocInferenceMapper - Class in org.apache.mahout.clustering.lda.cvb
 
CVB0DocInferenceMapper() - Constructor for class org.apache.mahout.clustering.lda.cvb.CVB0DocInferenceMapper
 
CVB0Driver - Class in org.apache.mahout.clustering.lda.cvb
See CachingCVB0Mapper for more details on scalability and room for improvement.
CVB0Driver() - Constructor for class org.apache.mahout.clustering.lda.cvb.CVB0Driver
 
CVB0Driver.DualDoubleSumReducer - Class in org.apache.mahout.clustering.lda.cvb
Sums keys and values independently.
CVB0Driver.DualDoubleSumReducer() - Constructor for class org.apache.mahout.clustering.lda.cvb.CVB0Driver.DualDoubleSumReducer
 
CVB0TopicTermVectorNormalizerMapper - Class in org.apache.mahout.clustering.lda.cvb
Performs L1 normalization of input vectors.
CVB0TopicTermVectorNormalizerMapper() - Constructor for class org.apache.mahout.clustering.lda.cvb.CVB0TopicTermVectorNormalizerMapper
 

D

Data - Class in org.apache.mahout.classifier.df.data
Holds a list of vectors and their corresponding Dataset.
Data(Dataset) - Constructor for class org.apache.mahout.classifier.df.data.Data
 
Data(Dataset, List<Instance>) - Constructor for class org.apache.mahout.classifier.df.data.Data
 
DataConverter - Class in org.apache.mahout.classifier.df.data
Converts String to Instance using a Dataset
DataConverter(Dataset) - Constructor for class org.apache.mahout.classifier.df.data.DataConverter
 
DataLoader - Class in org.apache.mahout.classifier.df.data
Converts the input data to a Vector Array using the information given by the Dataset.
Generates for each line a Vector that contains :
double parsed value for NUMERICAL attributes int value for CATEGORICAL and LABEL attributes
adds an IGNORED first attribute that will contain a unique id for each instance, which is the line number of the instance in the input data
DataModel - Interface in org.apache.mahout.cf.taste.model
Implementations represent a repository of information about users and their associated Preferences for items.
DataModelBuilder - Interface in org.apache.mahout.cf.taste.eval
Implementations of this inner interface are simple helper classes which create a DataModel to be used while evaluating a Recommender.
Dataset - Class in org.apache.mahout.classifier.df.data
Contains informations about the attributes.
Dataset.Attribute - Enum in org.apache.mahout.classifier.df.data
Attributes type
DatasetSplitter - Class in org.apache.mahout.cf.taste.hadoop.als
Split a recommendation dataset into a training and a test set
DatasetSplitter() - Constructor for class org.apache.mahout.cf.taste.hadoop.als.DatasetSplitter
 
Datastore - Interface in org.apache.mahout.classifier.bayes
The Datastore interface for the Algorithm to use
DataUtils - Class in org.apache.mahout.classifier.df.data
Helper methods that deals with data lists and arrays of values
DEBUG_OUTPUT - Static variable in class org.apache.mahout.common.commandline.MinhashOptionCreator
 
debugOutputOption() - Static method in class org.apache.mahout.common.commandline.MinhashOptionCreator
 
dec(int[], int[]) - Static method in class org.apache.mahout.classifier.df.data.DataUtils
foreach i : array1[i] -= array2[i]
decayExponent(double) - Method in class org.apache.mahout.classifier.sgd.CrossFoldLearner
 
decayExponent(double) - Method in class org.apache.mahout.classifier.sgd.OnlineLogisticRegression
 
DecisionForest - Class in org.apache.mahout.classifier.df
Represents a forest of decision trees.
DecisionForest(List<Node>) - Constructor for class org.apache.mahout.classifier.df.DecisionForest
 
DecisionTreeBuilder - Class in org.apache.mahout.classifier.df.builder
Builds a classification tree or regression tree
A classification tree is built when the criterion variable is the categorical attribute.
A regression tree is built when the criterion variable is the numerical attribute.
DecisionTreeBuilder() - Constructor for class org.apache.mahout.classifier.df.builder.DecisionTreeBuilder
 
decode(HmmModel, int[], boolean) - Static method in class org.apache.mahout.classifier.sequencelearning.hmm.HmmEvaluator
Returns the most likely sequence of hidden states for the given model and observation
decodeStateSequence(HmmModel, int[], boolean, String) - Static method in class org.apache.mahout.classifier.sequencelearning.hmm.HmmUtils
Decodes a given collection of state IDs into the corresponding state names registered in a given model.
decodeType(byte[], int) - Static method in class org.apache.mahout.vectorizer.collocations.llr.Gram
 
DEFAULT_CLUSTERED_POINTS_DIRECTORY - Static variable in class org.apache.mahout.clustering.canopy.CanopyDriver
 
DEFAULT_DATASOURCE_NAME - Static variable in class org.apache.mahout.cf.taste.impl.common.jdbc.AbstractJDBCComponent
 
DEFAULT_EMIT_UNIGRAMS - Static variable in class org.apache.mahout.vectorizer.collocations.llr.CollocDriver
 
DEFAULT_FACTOR - Static variable in class org.apache.mahout.cf.taste.impl.recommender.SamplingCandidateItemsStrategy
Default factor used if not otherwise specified, for all limits.
DEFAULT_LONG_ID_COLUMN - Static variable in class org.apache.mahout.cf.taste.impl.model.AbstractJDBCIDMigrator
 
DEFAULT_MAPPING_TABLE - Static variable in class org.apache.mahout.cf.taste.impl.model.AbstractJDBCIDMigrator
 
DEFAULT_MIN_LLR - Static variable in class org.apache.mahout.vectorizer.collocations.llr.LLRReducer
 
DEFAULT_MIN_RELOAD_INTERVAL_MS - Static variable in class org.apache.mahout.cf.taste.impl.model.file.FileDataModel
 
DEFAULT_MIN_RELOAD_INTERVAL_MS - Static variable in class org.apache.mahout.cf.taste.impl.model.file.FileIDMigrator
 
DEFAULT_MIN_RELOAD_INTERVAL_MS - Static variable in class org.apache.mahout.cf.taste.impl.similarity.file.FileItemSimilarity
 
DEFAULT_MIN_SUPPORT - Static variable in class org.apache.mahout.vectorizer.collocations.llr.CollocReducer
 
DEFAULT_MIN_SUPPORT - Static variable in class org.apache.mahout.vectorizer.DictionaryVectorizer
 
DEFAULT_POOL_SIZE - Static variable in class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression
 
DEFAULT_STRING_ID_COLUMN - Static variable in class org.apache.mahout.cf.taste.impl.model.AbstractJDBCIDMigrator
 
DEFAULT_THREAD_COUNT - Static variable in class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression
 
DefaultAnalyzer - Class in org.apache.mahout.vectorizer
A subclass of the Lucene StandardAnalyzer that provides a no-argument constructor.
DefaultAnalyzer() - Constructor for class org.apache.mahout.vectorizer.DefaultAnalyzer
 
DefaultGradient - Class in org.apache.mahout.classifier.sgd
Implements the basic logistic training law.
DefaultGradient() - Constructor for class org.apache.mahout.classifier.sgd.DefaultGradient
 
DefaultIgSplit - Class in org.apache.mahout.classifier.df.split
Default, not optimized, implementation of IgSplit
DefaultIgSplit() - Constructor for class org.apache.mahout.classifier.df.split.DefaultIgSplit
 
DefaultOptionCreator - Class in org.apache.mahout.common.commandline
 
DefaultTreeBuilder - Class in org.apache.mahout.classifier.df.builder
Builds a Decision Tree
Based on the algorithm described in the "Decision Trees" tutorials by Andrew W.
DefaultTreeBuilder() - Constructor for class org.apache.mahout.classifier.df.builder.DefaultTreeBuilder
 
defaultValue() - Method in class org.apache.mahout.common.parameters.AbstractParameter
 
defaultValue() - Method in interface org.apache.mahout.common.parameters.Parameter
 
defineTargetCategories(List<String>) - Method in class org.apache.mahout.classifier.sgd.CsvRecordFactory
Defines the values and thus the encoding of values of the target variables.
defineTargetCategories(List<String>) - Method in interface org.apache.mahout.classifier.sgd.RecordFactory
 
delegate() - Method in class org.apache.mahout.cf.taste.impl.common.jdbc.ResultSetIterator
 
delegate() - Method in class org.apache.mahout.common.iterator.CopyConstructorIterator
 
delegate() - Method in class org.apache.mahout.common.iterator.FixedSizeSamplingIterator
 
delegate() - Method in class org.apache.mahout.common.iterator.sequencefile.SequenceFileDirIterator
 
delegate() - Method in class org.apache.mahout.common.iterator.sequencefile.SequenceFileDirValueIterator
 
delegate() - Method in class org.apache.mahout.common.iterator.StableFixedSizeSamplingIterator
 
delegate() - Method in class org.apache.mahout.common.iterator.StringRecordIterator
 
delegate() - Method in class org.apache.mahout.fpm.pfpgrowth.convertors.TransactionIterator
 
delete(Configuration, Iterable<Path>) - Static method in class org.apache.mahout.common.HadoopUtil
 
delete(Configuration, Path...) - Static method in class org.apache.mahout.common.HadoopUtil
 
DELTA - Static variable in interface org.apache.mahout.clustering.spectral.eigencuts.EigencutsKeys
The normalization factor for computing the cut threshold
DenseBlockWritable - Class in org.apache.mahout.math.hadoop.stochasticsvd
Ad-hoc substitution for MatrixWritable.
DenseBlockWritable() - Constructor for class org.apache.mahout.math.hadoop.stochasticsvd.DenseBlockWritable
 
Describe - Class in org.apache.mahout.classifier.df.tools
Generates a file descriptor for a given dataset
description() - Method in class org.apache.mahout.common.parameters.AbstractParameter
 
description() - Method in interface org.apache.mahout.common.parameters.Parameter
 
DescriptorException - Exception in org.apache.mahout.classifier.df.data
Exception thrown when parsing a descriptor
DescriptorException(String) - Constructor for exception org.apache.mahout.classifier.df.data.DescriptorException
 
DescriptorUtils - Class in org.apache.mahout.classifier.df.data
Contains various methods that deal with descriptor strings
determineDelimiter(String) - Static method in class org.apache.mahout.cf.taste.impl.model.file.FileDataModel
 
DFUtils - Class in org.apache.mahout.classifier.df
Utility class that contains various helper methods
DIAGONAL_CACHE_INDEX - Static variable in interface org.apache.mahout.clustering.spectral.eigencuts.EigencutsKeys
Sets the SequenceFile index for the diagonal matrix.
DICTIONARY - Static variable in class org.apache.mahout.clustering.lda.cvb.CVB0Driver
 
Dictionary - Class in org.apache.mahout.vectorizer.encoders
Assigns integer codes to strings as they appear.
Dictionary() - Constructor for class org.apache.mahout.vectorizer.encoders.Dictionary
 
DictionaryVectorizer - Class in org.apache.mahout.vectorizer
This class converts a set of input documents in the sequence file format to vectors.
DiffStorage - Interface in org.apache.mahout.cf.taste.recommender.slopeone
Implementations store item-item preference diffs for a SlopeOneRecommender.
DIMENSION - Static variable in class org.apache.mahout.vectorizer.common.PartialVectorMerger
 
DirichletCluster - Class in org.apache.mahout.clustering.dirichlet
 
DirichletCluster(Cluster, double) - Constructor for class org.apache.mahout.clustering.dirichlet.DirichletCluster
 
DirichletCluster(Cluster) - Constructor for class org.apache.mahout.clustering.dirichlet.DirichletCluster
 
DirichletCluster() - Constructor for class org.apache.mahout.clustering.dirichlet.DirichletCluster
 
DirichletClusterer - Class in org.apache.mahout.clustering.dirichlet
Performs Bayesian mixture modeling.
DirichletClusterer(List<VectorWritable>, ModelDistribution<VectorWritable>, double, int, int, int) - Constructor for class org.apache.mahout.clustering.dirichlet.DirichletClusterer
Create a new instance on the sample data with the given additional parameters
DirichletClusterer(boolean, double) - Constructor for class org.apache.mahout.clustering.dirichlet.DirichletClusterer
This constructor only used by DirichletClusterMapper for setting up clustering params
DirichletClusterer(DirichletState) - Constructor for class org.apache.mahout.clustering.dirichlet.DirichletClusterer
This constructor is used by DirichletMapper and DirichletReducer for setting up their clusterer
DirichletClusteringPolicy - Class in org.apache.mahout.clustering
 
DirichletClusteringPolicy(int, double) - Constructor for class org.apache.mahout.clustering.DirichletClusteringPolicy
 
DirichletClusterMapper - Class in org.apache.mahout.clustering.dirichlet
 
DirichletClusterMapper() - Constructor for class org.apache.mahout.clustering.dirichlet.DirichletClusterMapper
 
DirichletDriver - Class in org.apache.mahout.clustering.dirichlet
 
DirichletDriver() - Constructor for class org.apache.mahout.clustering.dirichlet.DirichletDriver
 
DirichletMapper - Class in org.apache.mahout.clustering.dirichlet
 
DirichletMapper() - Constructor for class org.apache.mahout.clustering.dirichlet.DirichletMapper
 
DirichletReducer - Class in org.apache.mahout.clustering.dirichlet
 
DirichletReducer() - Constructor for class org.apache.mahout.clustering.dirichlet.DirichletReducer
 
DirichletState - Class in org.apache.mahout.clustering.dirichlet
 
DirichletState(ModelDistribution<VectorWritable>, int, double) - Constructor for class org.apache.mahout.clustering.dirichlet.DirichletState
 
DirichletState(DistributionDescription, int, double) - Constructor for class org.apache.mahout.clustering.dirichlet.DirichletState
 
distance(Vector, Vector) - Method in class org.apache.mahout.common.distance.ChebyshevDistanceMeasure
 
distance(double, Vector, Vector) - Method in class org.apache.mahout.common.distance.ChebyshevDistanceMeasure
 
distance(double[], double[]) - Static method in class org.apache.mahout.common.distance.CosineDistanceMeasure
 
distance(Vector, Vector) - Method in class org.apache.mahout.common.distance.CosineDistanceMeasure
 
distance(double, Vector, Vector) - Method in class org.apache.mahout.common.distance.CosineDistanceMeasure
 
distance(Vector, Vector) - Method in interface org.apache.mahout.common.distance.DistanceMeasure
Returns the distance metric applied to the arguments
distance(double, Vector, Vector) - Method in interface org.apache.mahout.common.distance.DistanceMeasure
Optimized version of distance metric for sparse vectors.
distance(Vector, Vector) - Method in class org.apache.mahout.common.distance.EuclideanDistanceMeasure
 
distance(double, Vector, Vector) - Method in class org.apache.mahout.common.distance.EuclideanDistanceMeasure
 
distance(Vector) - Method in class org.apache.mahout.common.distance.MahalanobisDistanceMeasure
 
distance(Vector, Vector) - Method in class org.apache.mahout.common.distance.MahalanobisDistanceMeasure
 
distance(double, Vector, Vector) - Method in class org.apache.mahout.common.distance.MahalanobisDistanceMeasure
 
distance(double[], double[]) - Static method in class org.apache.mahout.common.distance.ManhattanDistanceMeasure
 
distance(Vector, Vector) - Method in class org.apache.mahout.common.distance.ManhattanDistanceMeasure
 
distance(double, Vector, Vector) - Method in class org.apache.mahout.common.distance.ManhattanDistanceMeasure
 
distance(Vector, Vector) - Method in class org.apache.mahout.common.distance.MinkowskiDistanceMeasure
Math.pow is clever about integer-valued doubles
distance(double, Vector, Vector) - Method in class org.apache.mahout.common.distance.MinkowskiDistanceMeasure
 
distance(Vector, Vector) - Method in class org.apache.mahout.common.distance.SquaredEuclideanDistanceMeasure
 
distance(double, Vector, Vector) - Method in class org.apache.mahout.common.distance.SquaredEuclideanDistanceMeasure
 
distance(Vector, Vector) - Method in class org.apache.mahout.common.distance.TanimotoDistanceMeasure
Calculates the distance between two vectors.
distance(double, Vector, Vector) - Method in class org.apache.mahout.common.distance.TanimotoDistanceMeasure
 
distance(Vector, Vector) - Method in class org.apache.mahout.common.distance.WeightedEuclideanDistanceMeasure
 
distance(double, Vector, Vector) - Method in class org.apache.mahout.common.distance.WeightedEuclideanDistanceMeasure
 
distance(Vector, Vector) - Method in class org.apache.mahout.common.distance.WeightedManhattanDistanceMeasure
 
distance(double, Vector, Vector) - Method in class org.apache.mahout.common.distance.WeightedManhattanDistanceMeasure
 
DISTANCE_MEASURE_KEY - Static variable in interface org.apache.mahout.clustering.canopy.CanopyConfigKeys
 
DISTANCE_MEASURE_KEY - Static variable in interface org.apache.mahout.clustering.fuzzykmeans.FuzzyKMeansConfigKeys
 
DISTANCE_MEASURE_KEY - Static variable in interface org.apache.mahout.clustering.kmeans.KMeansConfigKeys
Configuration key for distance measure to use.
DISTANCE_MEASURE_KEY - Static variable in interface org.apache.mahout.clustering.meanshift.MeanShiftCanopyConfigKeys
 
DISTANCE_MEASURE_KEY - Static variable in class org.apache.mahout.math.hadoop.similarity.VectorDistanceSimilarityJob
 
DISTANCE_MEASURE_OPTION - Static variable in class org.apache.mahout.common.commandline.DefaultOptionCreator
 
DistanceMeasure - Interface in org.apache.mahout.common.distance
This interface is used for objects which can determine a distance metric between two points
DistanceMeasureCluster - Class in org.apache.mahout.clustering
 
DistanceMeasureCluster(Vector, int, DistanceMeasure) - Constructor for class org.apache.mahout.clustering.DistanceMeasureCluster
 
DistanceMeasureCluster() - Constructor for class org.apache.mahout.clustering.DistanceMeasureCluster
 
DistanceMeasureClusterDistribution - Class in org.apache.mahout.clustering.dirichlet.models
An implementation of the ModelDistribution interface suitable for testing the DirichletCluster algorithm.
DistanceMeasureClusterDistribution() - Constructor for class org.apache.mahout.clustering.dirichlet.models.DistanceMeasureClusterDistribution
 
DistanceMeasureClusterDistribution(VectorWritable) - Constructor for class org.apache.mahout.clustering.dirichlet.models.DistanceMeasureClusterDistribution
 
DistanceMeasureClusterDistribution(VectorWritable, DistanceMeasure) - Constructor for class org.apache.mahout.clustering.dirichlet.models.DistanceMeasureClusterDistribution
 
distanceMeasureOption() - Static method in class org.apache.mahout.common.commandline.DefaultOptionCreator
Returns a default command line option for specification of distance measure class to use.
DistributedConjugateGradientSolver - Class in org.apache.mahout.math.hadoop.solver
Distributed implementation of the conjugate gradient solver.
DistributedConjugateGradientSolver() - Constructor for class org.apache.mahout.math.hadoop.solver.DistributedConjugateGradientSolver
 
DistributedConjugateGradientSolver.DistributedConjugateGradientSolverJob - Class in org.apache.mahout.math.hadoop.solver
 
DistributedConjugateGradientSolver.DistributedConjugateGradientSolverJob() - Constructor for class org.apache.mahout.math.hadoop.solver.DistributedConjugateGradientSolver.DistributedConjugateGradientSolverJob
 
DistributedLanczosSolver - Class in org.apache.mahout.math.hadoop.decomposer
 
DistributedLanczosSolver() - Constructor for class org.apache.mahout.math.hadoop.decomposer.DistributedLanczosSolver
 
DistributedLanczosSolver.DistributedLanczosSolverJob - Class in org.apache.mahout.math.hadoop.decomposer
Inner subclass of AbstractJob so we get access to AbstractJob's functionality w.r.t.
DistributedLanczosSolver.DistributedLanczosSolverJob() - Constructor for class org.apache.mahout.math.hadoop.decomposer.DistributedLanczosSolver.DistributedLanczosSolverJob
 
DistributedRowMatrix - Class in org.apache.mahout.math.hadoop
DistributedRowMatrix is a FileSystem-backed VectorIterable in which the vectors live in a SequenceFile, and distributed operations are executed as M/R passes on Hadoop.
DistributedRowMatrix(Path, Path, int, int) - Constructor for class org.apache.mahout.math.hadoop.DistributedRowMatrix
 
DistributedRowMatrix(Path, Path, int, int, boolean) - Constructor for class org.apache.mahout.math.hadoop.DistributedRowMatrix
 
DistributedRowMatrix.MatrixEntryWritable - Class in org.apache.mahout.math.hadoop
 
DistributedRowMatrix.MatrixEntryWritable() - Constructor for class org.apache.mahout.math.hadoop.DistributedRowMatrix.MatrixEntryWritable
 
DistributedRowMatrixWriter - Class in org.apache.mahout.math
 
DistributionDescription - Class in org.apache.mahout.clustering.dirichlet.models
Simply describes parameters needs to create a ModelDistribution.
DistributionDescription(String, String, String, int) - Constructor for class org.apache.mahout.clustering.dirichlet.models.DistributionDescription
 
dNorm(double, double, double) - Static method in class org.apache.mahout.clustering.dirichlet.UncommonDistributions
Return the normal density function value for the sample x pdf = 1/[sqrt(2*p)*s] * e^{-1/2*[(x-m)/s]^2}
DOC_TOPIC_OUTPUT - Static variable in class org.apache.mahout.clustering.lda.cvb.CVB0Driver
 
DOC_TOPIC_SMOOTHING - Static variable in class org.apache.mahout.clustering.lda.cvb.CVB0Driver
 
DOCUMENT_FREQUENCY - Static variable in class org.apache.mahout.classifier.bayes.mapreduce.common.BayesConstants
 
DOCUMENT_VECTOR_OUTPUT_FOLDER - Static variable in class org.apache.mahout.vectorizer.DictionaryVectorizer
 
DocumentProcessor - Class in org.apache.mahout.vectorizer
This class converts a set of input documents in the sequence file format of StringTuples.The SequenceFile input should have a Text key containing the unique document identifier and a Text value containing the whole document.
documentWeight(Datastore, String, String[]) - Method in interface org.apache.mahout.classifier.bayes.Algorithm
Calculate the document weight as the dot product of document vector and the corresponding weight vector of a particular class
documentWeight(Datastore, String, String[]) - Method in class org.apache.mahout.classifier.bayes.BayesAlgorithm
 
documentWeight(Datastore, String, String[]) - Method in class org.apache.mahout.classifier.bayes.CBayesAlgorithm
 
doEstimatePreference(long, PreferenceArray, long) - Method in class org.apache.mahout.cf.taste.impl.recommender.GenericBooleanPrefItemBasedRecommender
This computation is in a technical sense, wrong, since in the domain of "boolean preference users" where all preference values are 1, this method should only ever return 1.0 or NaN.
doEstimatePreference(long, long[], long) - Method in class org.apache.mahout.cf.taste.impl.recommender.GenericBooleanPrefUserBasedRecommender
This computation is in a technical sense, wrong, since in the domain of "boolean preference users" where all preference values are 1, this method should only ever return 1.0 or NaN.
doEstimatePreference(long, PreferenceArray, long) - Method in class org.apache.mahout.cf.taste.impl.recommender.GenericItemBasedRecommender
 
doEstimatePreference(long, long[], long) - Method in class org.apache.mahout.cf.taste.impl.recommender.GenericUserBasedRecommender
 
doEstimatePreference(long, PreferenceArray, long) - Method in class org.apache.mahout.cf.taste.impl.recommender.knn.KnnItemBasedRecommender
 
doGetCandidateItems(long[], DataModel) - Method in class org.apache.mahout.cf.taste.impl.recommender.AllUnknownItemsCandidateItemsStrategy
return all items the user has not yet seen
doGetCandidateItems(long[], DataModel) - Method in class org.apache.mahout.cf.taste.impl.recommender.PreferredItemsNeighborhoodCandidateItemsStrategy
returns all items that have not been rated by the user and that were preferred by another user that has preferred at least one item that the current user has preferred too
doGetCandidateItems(long[], DataModel) - Method in class org.apache.mahout.cf.taste.impl.recommender.SamplingCandidateItemsStrategy
 
dot(Vector, Vector) - Method in class org.apache.mahout.common.distance.TanimotoDistanceMeasure
 
DoubleParameter - Class in org.apache.mahout.common.parameters
 
DoubleParameter(String, String, Configuration, double, String) - Constructor for class org.apache.mahout.common.parameters.DoubleParameter
 
DoubleSumReducer - Class in org.apache.mahout.math.stats.entropy
Analog of org.apache.hadoop.mapreduce.lib.reduce.IntSumReducer which sums the double values.
DoubleSumReducer() - Constructor for class org.apache.mahout.math.stats.entropy.DoubleSumReducer
 

E

EigencutsAffinityCutsJob - Class in org.apache.mahout.clustering.spectral.eigencuts
 
EigencutsAffinityCutsJob.EigencutsAffinityCutsCombiner - Class in org.apache.mahout.clustering.spectral.eigencuts
 
EigencutsAffinityCutsJob.EigencutsAffinityCutsCombiner() - Constructor for class org.apache.mahout.clustering.spectral.eigencuts.EigencutsAffinityCutsJob.EigencutsAffinityCutsCombiner
 
EigencutsAffinityCutsJob.EigencutsAffinityCutsMapper - Class in org.apache.mahout.clustering.spectral.eigencuts
 
EigencutsAffinityCutsJob.EigencutsAffinityCutsMapper() - Constructor for class org.apache.mahout.clustering.spectral.eigencuts.EigencutsAffinityCutsJob.EigencutsAffinityCutsMapper
 
EigencutsAffinityCutsJob.EigencutsAffinityCutsReducer - Class in org.apache.mahout.clustering.spectral.eigencuts
 
EigencutsAffinityCutsJob.EigencutsAffinityCutsReducer() - Constructor for class org.apache.mahout.clustering.spectral.eigencuts.EigencutsAffinityCutsJob.EigencutsAffinityCutsReducer
 
EigencutsDriver - Class in org.apache.mahout.clustering.spectral.eigencuts
 
EigencutsDriver() - Constructor for class org.apache.mahout.clustering.spectral.eigencuts.EigencutsDriver
 
EigencutsKeys - Interface in org.apache.mahout.clustering.spectral.eigencuts
Configuration keys for the Eigencuts algorithm (analogous to KMeansConfigKeys)
EigencutsSensitivityJob - Class in org.apache.mahout.clustering.spectral.eigencuts
There are a quite a few operations bundled within this mapper.
EigencutsSensitivityMapper - Class in org.apache.mahout.clustering.spectral.eigencuts
 
EigencutsSensitivityMapper() - Constructor for class org.apache.mahout.clustering.spectral.eigencuts.EigencutsSensitivityMapper
 
EigencutsSensitivityNode - Class in org.apache.mahout.clustering.spectral.eigencuts
This class allows the storage of computed sensitivities in an unordered fashion, instead having each sensitivity track its own (i, j) coordinate.
EigencutsSensitivityNode(int, int, double) - Constructor for class org.apache.mahout.clustering.spectral.eigencuts.EigencutsSensitivityNode
 
EigencutsSensitivityReducer - Class in org.apache.mahout.clustering.spectral.eigencuts
The point of this class is to take all the arrays of sensitivities and convert them to a single matrix.
EigencutsSensitivityReducer() - Constructor for class org.apache.mahout.clustering.spectral.eigencuts.EigencutsSensitivityReducer
 
EIGENVALUES_CACHE_INDEX - Static variable in interface org.apache.mahout.clustering.spectral.eigencuts.EigencutsKeys
Sets the SequenceFile index for the list of eigenvalues.
EigenVector - Class in org.apache.mahout.math.hadoop.decomposer
TODO this is a horrible hack.
EigenVector(Vector, double, double, int) - Constructor for class org.apache.mahout.math.hadoop.decomposer.EigenVector
 
EigenVerificationJob - Class in org.apache.mahout.math.hadoop.decomposer
Class for taking the output of an eigendecomposition (specified as a Path location), and verifies correctness, in terms of the following: if you have a vector e, and a matrix m, then let e' = m.timesSquared(v); the error w.r.t.
EigenVerificationJob() - Constructor for class org.apache.mahout.math.hadoop.decomposer.EigenVerificationJob
 
elapsedTime(long) - Static method in class org.apache.mahout.classifier.df.DFUtils
Formats a time interval in milliseconds to a String in the form "hours:minutes:seconds:millis"
ElasticBandPrior - Class in org.apache.mahout.classifier.sgd
Implements a linear combination of L1 and L2 priors.
ElasticBandPrior() - Constructor for class org.apache.mahout.classifier.sgd.ElasticBandPrior
 
ElasticBandPrior(double) - Constructor for class org.apache.mahout.classifier.sgd.ElasticBandPrior
 
EMIT_MOST_LIKELY_KEY - Static variable in class org.apache.mahout.clustering.dirichlet.DirichletDriver
 
EMIT_MOST_LIKELY_KEY - Static variable in interface org.apache.mahout.clustering.fuzzykmeans.FuzzyKMeansConfigKeys
 
EMIT_MOST_LIKELY_OPTION - Static variable in class org.apache.mahout.common.commandline.DefaultOptionCreator
 
EMIT_UNIGRAMS - Static variable in class org.apache.mahout.vectorizer.collocations.llr.CollocDriver
 
emitMostLikelyOption() - Static method in class org.apache.mahout.common.commandline.DefaultOptionCreator
Returns a default command line option for specifying the emitMostLikely flag.
emitPointProbToCluster(Vector, List<SoftCluster>, Mapper<?, ?, Text, ClusterObservations>.Context) - Method in class org.apache.mahout.clustering.fuzzykmeans.FuzzyKMeansClusterer
Emit the point and its probability of belongingness to each cluster
emitPointToClosestCanopy(Vector, Iterable<Canopy>, Mapper<?, ?, IntWritable, WeightedVectorWritable>.Context) - Method in class org.apache.mahout.clustering.canopy.CanopyClusterer
Emit the point to the closest Canopy
emitPointToClusters(VectorWritable, List<DirichletCluster>, Mapper<?, ?, IntWritable, WeightedVectorWritable>.Context) - Method in class org.apache.mahout.clustering.dirichlet.DirichletClusterer
Emit the point to one or more clusters depending upon clusterer state
emitPointToClusters(VectorWritable, List<DirichletCluster>, SequenceFile.Writer) - Method in class org.apache.mahout.clustering.dirichlet.DirichletClusterer
Emit the point to one or more clusters depending upon clusterer state
emitPointToClusters(VectorWritable, List<SoftCluster>, Mapper<?, ?, IntWritable, WeightedVectorWritable>.Context) - Method in class org.apache.mahout.clustering.fuzzykmeans.FuzzyKMeansClusterer
 
emitPointToClusters(VectorWritable, List<SoftCluster>, SequenceFile.Writer) - Method in class org.apache.mahout.clustering.fuzzykmeans.FuzzyKMeansClusterer
 
emitPointToNearestCluster(Vector, Iterable<Cluster>, Mapper<?, ?, Text, ClusterObservations>.Context) - Method in class org.apache.mahout.clustering.kmeans.KMeansClusterer
Iterates over all clusters and identifies the one closes to the given point.
emitPointToNearestCluster(Vector, Iterable<Cluster>, SequenceFile.Writer) - Method in class org.apache.mahout.clustering.kmeans.KMeansClusterer
Iterates over all clusters and identifies the one closes to the given point.
emitRow(int, Vector) - Method in interface org.apache.mahout.math.hadoop.stochasticsvd.PartialRowEmitter
 
EncodedVectorsFromSequenceFiles - Class in org.apache.mahout.vectorizer
Converts a given set of sequence files into SparseVectors
EncodedVectorsFromSequenceFiles() - Constructor for class org.apache.mahout.vectorizer.EncodedVectorsFromSequenceFiles
 
ENCODER_CLASS - Static variable in class org.apache.mahout.vectorizer.EncodingMapper
 
ENCODER_FIELD_NAME - Static variable in class org.apache.mahout.vectorizer.EncodingMapper
 
encodeStateSequence(HmmModel, Collection<String>, boolean, int) - Static method in class org.apache.mahout.classifier.sequencelearning.hmm.HmmUtils
Encodes a given collection of state names by the corresponding state IDs registered in a given model.
encodeType(Gram.Type, byte[], int) - Static method in class org.apache.mahout.vectorizer.collocations.llr.Gram
 
ENCODING - Static variable in class org.apache.mahout.fpm.pfpgrowth.PFPGrowth
 
EncodingMapper - Class in org.apache.mahout.vectorizer
The Mapper that does the work of encoding text
EncodingMapper() - Constructor for class org.apache.mahout.vectorizer.EncodingMapper
 
end() - Method in class org.apache.mahout.common.TimingStatistics.Call
 
EntityCountWritable - Class in org.apache.mahout.cf.taste.hadoop
A Writable encapsulating an item ID and a count .
EntityCountWritable() - Constructor for class org.apache.mahout.cf.taste.hadoop.EntityCountWritable
 
EntityCountWritable(long, int) - Constructor for class org.apache.mahout.cf.taste.hadoop.EntityCountWritable
 
EntityCountWritable(EntityCountWritable) - Constructor for class org.apache.mahout.cf.taste.hadoop.EntityCountWritable
 
EntityEntityWritable - Class in org.apache.mahout.cf.taste.hadoop
A WritableComparable encapsulating two items.
EntityEntityWritable() - Constructor for class org.apache.mahout.cf.taste.hadoop.EntityEntityWritable
 
EntityEntityWritable(long, long) - Constructor for class org.apache.mahout.cf.taste.hadoop.EntityEntityWritable
 
EntityPrefWritable - Class in org.apache.mahout.cf.taste.hadoop
A Writable encapsulating an item ID and a preference value.
EntityPrefWritable() - Constructor for class org.apache.mahout.cf.taste.hadoop.EntityPrefWritable
 
EntityPrefWritable(long, float) - Constructor for class org.apache.mahout.cf.taste.hadoop.EntityPrefWritable
 
EntityPrefWritable(EntityPrefWritable) - Constructor for class org.apache.mahout.cf.taste.hadoop.EntityPrefWritable
 
EntityPrefWritableArrayWritable - Class in org.apache.mahout.cf.taste.hadoop
An ArrayWritable holding EntityPrefWritables
EntityPrefWritableArrayWritable() - Constructor for class org.apache.mahout.cf.taste.hadoop.EntityPrefWritableArrayWritable
 
EntityPrefWritableArrayWritable(EntityPrefWritable[]) - Constructor for class org.apache.mahout.cf.taste.hadoop.EntityPrefWritableArrayWritable
 
entropy(Data) - Method in class org.apache.mahout.classifier.df.split.DefaultIgSplit
Computes the Entropy
entropy() - Method in class org.apache.mahout.classifier.evaluation.Auc
Returns a matrix related to the confusion matrix and to the log-likelihood.
Entropy - Class in org.apache.mahout.math.stats.entropy
A Hadoop job to compute the entropy of keys or values in a SequenceFile.
Entropy() - Constructor for class org.apache.mahout.math.stats.entropy.Entropy
 
entrySet() - Method in class org.apache.mahout.cf.taste.impl.common.FastByIDMap
 
entrySet() - Method in class org.apache.mahout.cf.taste.impl.common.FastMap
 
EPSILON - Static variable in interface org.apache.mahout.clustering.spectral.eigencuts.EigencutsKeys
Epsilon, or the user-specified coefficient that works in tandem with MINIMUM_HALF_LIFE to determine which eigenvector/eigenvalue pairs to use.
EPSILON_DEFAULT - Static variable in class org.apache.mahout.clustering.spectral.eigencuts.EigencutsDriver
 
equals(Object) - Method in class org.apache.mahout.cf.taste.hadoop.EntityCountWritable
 
equals(Object) - Method in class org.apache.mahout.cf.taste.hadoop.EntityEntityWritable
 
equals(Object) - Method in class org.apache.mahout.cf.taste.hadoop.EntityPrefWritable
 
equals(Object) - Method in class org.apache.mahout.cf.taste.hadoop.item.PrefAndSimilarityColumnWritable
 
equals(Object) - Method in class org.apache.mahout.cf.taste.impl.common.FastByIDMap
 
equals(Object) - Method in class org.apache.mahout.cf.taste.impl.common.FastIDSet
 
equals(Object) - Method in class org.apache.mahout.cf.taste.impl.common.FastMap
 
equals(Object) - Method in class org.apache.mahout.cf.taste.impl.model.BooleanItemPreferenceArray
 
equals(Object) - Method in class org.apache.mahout.cf.taste.impl.model.BooleanUserPreferenceArray
 
equals(Object) - Method in class org.apache.mahout.cf.taste.impl.model.GenericItemPreferenceArray
 
equals(Object) - Method in class org.apache.mahout.cf.taste.impl.model.GenericUserPreferenceArray
 
equals(Object) - Method in class org.apache.mahout.cf.taste.impl.recommender.GenericRecommendedItem
 
equals(Object) - Method in class org.apache.mahout.cf.taste.impl.recommender.SimilarUser
 
equals(Object) - Method in class org.apache.mahout.cf.taste.impl.recommender.svd.Factorization
 
equals(Object) - Method in class org.apache.mahout.cf.taste.impl.similarity.GenericItemSimilarity.ItemItemSimilarity
 
equals(Object) - Method in class org.apache.mahout.cf.taste.impl.similarity.GenericUserSimilarity.UserUserSimilarity
 
equals(int, double) - Static method in class org.apache.mahout.classifier.df.data.conditions.Condition
Condition that checks if the given attribute has a value "equal" to the given value
Equals - Class in org.apache.mahout.classifier.df.data.conditions
True if a given attribute has a given value
Equals(int, double) - Constructor for class org.apache.mahout.classifier.df.data.conditions.Equals
 
equals(Object) - Method in class org.apache.mahout.classifier.df.data.Data
 
equals(Object) - Method in class org.apache.mahout.classifier.df.data.Dataset
 
equals(Object) - Method in class org.apache.mahout.classifier.df.data.Instance
 
equals(Object) - Method in class org.apache.mahout.classifier.df.DecisionForest
 
equals(Object) - Method in class org.apache.mahout.classifier.df.mapreduce.inmem.InMemInputFormat.InMemInputSplit
 
equals(Object) - Method in class org.apache.mahout.classifier.df.mapreduce.MapredOutput
 
equals(Object) - Method in class org.apache.mahout.classifier.df.node.CategoricalNode
 
equals(Object) - Method in class org.apache.mahout.classifier.df.node.Leaf
 
equals(Object) - Method in class org.apache.mahout.classifier.df.node.NumericalNode
 
equals(Object) - Method in class org.apache.mahout.classifier.sgd.ModelDissector.Weight
 
equals(Object) - Method in class org.apache.mahout.common.IntegerTuple
 
equals(Object) - Method in class org.apache.mahout.common.IntPairWritable
 
equals(Object) - Method in class org.apache.mahout.common.IntPairWritable.Frequency
 
equals(Object) - Method in class org.apache.mahout.common.IntTuple
 
equals(Object) - Method in class org.apache.mahout.common.LongPair
 
equals(Object) - Method in class org.apache.mahout.common.Pair
 
equals(Object) - Method in class org.apache.mahout.common.StringTuple
 
equals(Object) - Method in class org.apache.mahout.ep.State
 
equals(Object) - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.Pattern
 
equals(Object) - Method in class org.apache.mahout.math.hadoop.DistributedRowMatrix.MatrixEntryWritable
 
equals(Object) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.SplitPartitionedWritable
 
equals(Object) - Method in class org.apache.mahout.math.VarIntWritable
 
equals(Object) - Method in class org.apache.mahout.math.VarLongWritable
 
equals(Object) - Method in class org.apache.mahout.math.VectorWritable
 
ErrorEstimate - Class in org.apache.mahout.classifier.df
Various methods to compute from the output of a random forest
errorRate(double[], double[]) - Static method in class org.apache.mahout.classifier.df.ErrorEstimate
 
escapeXML(String) - Static method in class org.apache.mahout.common.StringUtils
 
estimate(Long) - Method in class org.apache.mahout.cf.taste.impl.recommender.GenericItemBasedRecommender.MostSimilarEstimator
 
estimate(T) - Method in interface org.apache.mahout.cf.taste.impl.recommender.TopItems.Estimator
 
EstimatedPreferenceCapper - Class in org.apache.mahout.cf.taste.impl.recommender
Simple class which encapsulates restricting a preference value to a predefined range.
EstimatedPreferenceCapper(DataModel) - Constructor for class org.apache.mahout.cf.taste.impl.recommender.EstimatedPreferenceCapper
 
estimatePreference(long, long) - Method in class org.apache.mahout.cf.taste.impl.recommender.CachingRecommender
 
estimatePreference(long, long) - Method in class org.apache.mahout.cf.taste.impl.recommender.GenericItemBasedRecommender
 
estimatePreference(long, long) - Method in class org.apache.mahout.cf.taste.impl.recommender.GenericUserBasedRecommender
 
estimatePreference(long, long) - Method in class org.apache.mahout.cf.taste.impl.recommender.ItemAverageRecommender
 
estimatePreference(long, long) - Method in class org.apache.mahout.cf.taste.impl.recommender.ItemUserAverageRecommender
 
estimatePreference(long, long) - Method in class org.apache.mahout.cf.taste.impl.recommender.RandomRecommender
 
estimatePreference(long, long) - Method in class org.apache.mahout.cf.taste.impl.recommender.slopeone.SlopeOneRecommender
 
estimatePreference(long, long) - Method in class org.apache.mahout.cf.taste.impl.recommender.svd.SVDRecommender
a preference is estimated by computing the dot-product of the user and item feature vectors
estimatePreference(long, long) - Method in class org.apache.mahout.cf.taste.impl.recommender.TreeClusteringRecommender
 
estimatePreference(long, long) - Method in class org.apache.mahout.cf.taste.impl.recommender.TreeClusteringRecommender2
 
estimatePreference(long, long) - Method in interface org.apache.mahout.cf.taste.recommender.Recommender
 
EuclideanDistanceMeasure - Class in org.apache.mahout.common.distance
This class implements a Euclidean distance metric by summing the square root of the squared differences between each coordinate.
EuclideanDistanceMeasure() - Constructor for class org.apache.mahout.common.distance.EuclideanDistanceMeasure
 
EuclideanDistanceSimilarity - Class in org.apache.mahout.cf.taste.impl.similarity
An implementation of a "similarity" based on the Euclidean "distance" between two users X and Y.
EuclideanDistanceSimilarity(DataModel) - Constructor for class org.apache.mahout.cf.taste.impl.similarity.EuclideanDistanceSimilarity
 
EuclideanDistanceSimilarity(DataModel, Weighting) - Constructor for class org.apache.mahout.cf.taste.impl.similarity.EuclideanDistanceSimilarity
 
EuclideanDistanceSimilarity - Class in org.apache.mahout.math.hadoop.similarity.cooccurrence.measures
 
EuclideanDistanceSimilarity() - Constructor for class org.apache.mahout.math.hadoop.similarity.cooccurrence.measures.EuclideanDistanceSimilarity
 
EvalMapper - Class in org.apache.mahout.ga.watchmaker
Generic Mapper class for fitness evaluation.
EvalMapper() - Constructor for class org.apache.mahout.ga.watchmaker.EvalMapper
 
evaluate(RecommenderBuilder, DataModelBuilder, DataModel, double, double) - Method in interface org.apache.mahout.cf.taste.eval.RecommenderEvaluator
Evaluates the quality of a Recommender's recommendations.
evaluate(RecommenderBuilder, DataModelBuilder, DataModel, IDRescorer, int, double, double) - Method in interface org.apache.mahout.cf.taste.eval.RecommenderIRStatsEvaluator
 
evaluate(RecommenderBuilder, DataModelBuilder, DataModel, double, double) - Method in class org.apache.mahout.cf.taste.impl.eval.AbstractDifferenceRecommenderEvaluator
 
evaluate(RecommenderBuilder, DataModelBuilder, DataModel, IDRescorer, int, double, double) - Method in class org.apache.mahout.cf.taste.impl.eval.GenericRecommenderIRStatsEvaluator
 
evaluate(Recommender, Recommender, int, RunningAverage, String) - Static method in class org.apache.mahout.cf.taste.impl.eval.OrderBasedRecommenderEvaluator
 
evaluate(Recommender, DataModel, int, RunningAverage, String) - Static method in class org.apache.mahout.cf.taste.impl.eval.OrderBasedRecommenderEvaluator
 
evaluate(DataModel, DataModel, int, RunningAverage, String) - Static method in class org.apache.mahout.cf.taste.impl.eval.OrderBasedRecommenderEvaluator
 
evaluate(FitnessEvaluator<?>, Iterable<?>, Collection<Double>, Path, Path) - Static method in class org.apache.mahout.ga.watchmaker.MahoutEvaluator
Uses Mahout to evaluate every candidate from the input population using the given evaluator.
evaluate(List<? extends T>, List<Double>) - Method in class org.apache.mahout.ga.watchmaker.MahoutFitnessEvaluator
 
evaluate(List<? extends T>, List<Double>) - Method in class org.apache.mahout.ga.watchmaker.STFitnessEvaluator
 
evaluatePopulation(List<T>) - Method in class org.apache.mahout.ga.watchmaker.STEvolutionEngine
 
evaluateSpecificOptions(Map<String, String>) - Method in class org.apache.mahout.graph.linkanalysis.RandomWalkWithRestartJob
 
EvolutionaryProcess<T extends Payload<U>,U> - Class in org.apache.mahout.ep
Allows evolutionary optimization where the state function can't be easily packaged for the optimizer to execute.
EvolutionaryProcess() - Constructor for class org.apache.mahout.ep.EvolutionaryProcess
 
EvolutionaryProcess(int, int, State<T, U>) - Constructor for class org.apache.mahout.ep.EvolutionaryProcess
Creates an evolutionary optimization framework with specified threadiness, population size and initial state.
EvolutionaryProcess.Function<T> - Interface in org.apache.mahout.ep
 
execute(Collection<Callable<Void>>, AtomicInteger, RunningAverageAndStdDev) - Static method in class org.apache.mahout.cf.taste.impl.eval.AbstractDifferenceRecommenderEvaluator
 
execute(String[], BayesJob) - Static method in class org.apache.mahout.classifier.bayes.mapreduce.common.JobExecutor
Execute a bayes classification job.
ExpectationMaximizationSVDFactorizer - Class in org.apache.mahout.cf.taste.impl.recommender.svd
Calculates the SVD using an Expectation Maximization algorithm.
ExpectationMaximizationSVDFactorizer(DataModel, int, int) - Constructor for class org.apache.mahout.cf.taste.impl.recommender.svd.ExpectationMaximizationSVDFactorizer
 
ExpectationMaximizationSVDFactorizer(DataModel, int, double, double, double, int) - Constructor for class org.apache.mahout.cf.taste.impl.recommender.svd.ExpectationMaximizationSVDFactorizer
 
exponential() - Static method in class org.apache.mahout.ep.Mapping
Maps results to positive values.
exponential(double) - Static method in class org.apache.mahout.ep.Mapping
Maps results to positive values.
exportWithIDsOnly() - Method in interface org.apache.mahout.cf.taste.model.JDBCDataModel
 
exportWithPrefs() - Method in interface org.apache.mahout.cf.taste.model.JDBCDataModel
Hmm, should this exist elsewhere? seems like most relevant for a DB implementation, which is not in memory, which might want to export to memory.
extractLabels() - Method in class org.apache.mahout.classifier.df.data.Data
extract the labels of all instances

F

F_LIST - Static variable in class org.apache.mahout.fpm.pfpgrowth.PFPGrowth
 
Factorization - Class in org.apache.mahout.cf.taste.impl.recommender.svd
a factorization of the rating matrix
Factorization(FastByIDMap<Integer>, FastByIDMap<Integer>, double[][], double[][]) - Constructor for class org.apache.mahout.cf.taste.impl.recommender.svd.Factorization
 
FactorizationEvaluator - Class in org.apache.mahout.cf.taste.hadoop.als
Measures the root-mean-squared error of a ratring matrix factorization against a test set.
FactorizationEvaluator() - Constructor for class org.apache.mahout.cf.taste.hadoop.als.FactorizationEvaluator
 
FactorizationEvaluator.PredictRatingsMapper - Class in org.apache.mahout.cf.taste.hadoop.als
 
FactorizationEvaluator.PredictRatingsMapper() - Constructor for class org.apache.mahout.cf.taste.hadoop.als.FactorizationEvaluator.PredictRatingsMapper
 
factorize() - Method in class org.apache.mahout.cf.taste.impl.recommender.svd.ALSWRFactorizer
 
factorize() - Method in class org.apache.mahout.cf.taste.impl.recommender.svd.ExpectationMaximizationSVDFactorizer
 
factorize() - Method in interface org.apache.mahout.cf.taste.impl.recommender.svd.Factorizer
 
Factorizer - Interface in org.apache.mahout.cf.taste.impl.recommender.svd
Implementation must be able to create a factorization of a rating matrix
FarthestNeighborClusterSimilarity - Class in org.apache.mahout.cf.taste.impl.recommender
Defines cluster similarity as the smallest similarity between any two users in the clusters -- that is, it says that clusters are close when all pairs of their members have relatively high similarity.
FarthestNeighborClusterSimilarity(UserSimilarity) - Constructor for class org.apache.mahout.cf.taste.impl.recommender.FarthestNeighborClusterSimilarity
Constructs a based on the given UserSimilarity.
FarthestNeighborClusterSimilarity(UserSimilarity, double) - Constructor for class org.apache.mahout.cf.taste.impl.recommender.FarthestNeighborClusterSimilarity
Constructs a based on the given UserSimilarity.
FastByIDMap<V> - Class in org.apache.mahout.cf.taste.impl.common
 
FastByIDMap() - Constructor for class org.apache.mahout.cf.taste.impl.common.FastByIDMap
Creates a new with default capacity.
FastByIDMap(int) - Constructor for class org.apache.mahout.cf.taste.impl.common.FastByIDMap
 
FastByIDMap(int, int) - Constructor for class org.apache.mahout.cf.taste.impl.common.FastByIDMap
Creates a new whose capacity can accommodate the given number of entries without rehash.
FastIDSet - Class in org.apache.mahout.cf.taste.impl.common
 
FastIDSet() - Constructor for class org.apache.mahout.cf.taste.impl.common.FastIDSet
Creates a new with default capacity.
FastIDSet(long[]) - Constructor for class org.apache.mahout.cf.taste.impl.common.FastIDSet
 
FastIDSet(int) - Constructor for class org.apache.mahout.cf.taste.impl.common.FastIDSet
 
FastMap<K,V> - Class in org.apache.mahout.cf.taste.impl.common
This is an optimized Map implementation, based on algorithms described in Knuth's "Art of Computer Programming", Vol.
FastMap() - Constructor for class org.apache.mahout.cf.taste.impl.common.FastMap
Creates a new with default capacity.
FastMap(int) - Constructor for class org.apache.mahout.cf.taste.impl.common.FastMap
 
FastMap(Map<K, V>) - Constructor for class org.apache.mahout.cf.taste.impl.common.FastMap
 
FastMap(int, int) - Constructor for class org.apache.mahout.cf.taste.impl.common.FastMap
Creates a new whose capacity can accommodate the given number of entries without rehash.
FEATURE_COUNT - Static variable in class org.apache.mahout.classifier.bayes.mapreduce.common.BayesConstants
 
FEATURE_COUNT - Static variable in class org.apache.mahout.vectorizer.tfidf.TFIDFConverter
 
FEATURE_SET_SIZE - Static variable in class org.apache.mahout.classifier.bayes.mapreduce.common.BayesConstants
 
FEATURE_SUM - Static variable in class org.apache.mahout.classifier.bayes.mapreduce.common.BayesConstants
 
FEATURE_TF - Static variable in class org.apache.mahout.classifier.bayes.mapreduce.common.BayesConstants
 
FeatureLabelComparator - Class in org.apache.mahout.classifier.bayes.mapreduce.common
 
FeatureLabelComparator() - Constructor for class org.apache.mahout.classifier.bayes.mapreduce.common.FeatureLabelComparator
 
FeaturePartitioner - Class in org.apache.mahout.classifier.bayes.mapreduce.common
ensure that features all make it into the same partition.
FeaturePartitioner() - Constructor for class org.apache.mahout.classifier.bayes.mapreduce.common.FeaturePartitioner
 
FeatureVectorEncoder - Class in org.apache.mahout.vectorizer.encoders
General interface for objects that record features into a feature vector.
FeatureVectorEncoder(String) - Constructor for class org.apache.mahout.vectorizer.encoders.FeatureVectorEncoder
 
FeatureVectorEncoder(String, int) - Constructor for class org.apache.mahout.vectorizer.encoders.FeatureVectorEncoder
 
featureWeight(Datastore, String, String) - Method in interface org.apache.mahout.classifier.bayes.Algorithm
Get the weighted probability of the feature.
featureWeight(Datastore, String, String) - Method in class org.apache.mahout.classifier.bayes.BayesAlgorithm
 
featureWeight(Datastore, String, String) - Method in class org.apache.mahout.classifier.bayes.CBayesAlgorithm
 
featureWeight(int) - Method in class org.apache.mahout.classifier.naivebayes.NaiveBayesModel
 
featureWeight(int) - Method in class org.apache.mahout.classifier.naivebayes.training.AbstractThetaTrainer
 
fetchVector(Path, int) - Method in class org.apache.mahout.math.hadoop.decomposer.HdfsBackedLanczosState
 
FILE_PATTERN - Static variable in class org.apache.mahout.fpm.pfpgrowth.PFPGrowth
 
FileDataModel - Class in org.apache.mahout.cf.taste.impl.model.file
A DataModel backed by a delimited file.
FileDataModel(File) - Constructor for class org.apache.mahout.cf.taste.impl.model.file.FileDataModel
 
FileDataModel(File, boolean, long) - Constructor for class org.apache.mahout.cf.taste.impl.model.file.FileDataModel
 
FileDiffStorage - Class in org.apache.mahout.cf.taste.impl.recommender.slopeone.file
DiffStorage which reads pre-computed diffs from a file and stores in memory.
FileDiffStorage(File, long) - Constructor for class org.apache.mahout.cf.taste.impl.recommender.slopeone.file.FileDiffStorage
 
FileIDMigrator - Class in org.apache.mahout.cf.taste.impl.model.file
An IDMigrator backed by a file.
FileIDMigrator(File) - Constructor for class org.apache.mahout.cf.taste.impl.model.file.FileIDMigrator
 
FileIDMigrator(File, long) - Constructor for class org.apache.mahout.cf.taste.impl.model.file.FileIDMigrator
 
FileItemSimilarity - Class in org.apache.mahout.cf.taste.impl.similarity.file
An ItemSimilarity backed by a comma-delimited file.
FileItemSimilarity(File) - Constructor for class org.apache.mahout.cf.taste.impl.similarity.file.FileItemSimilarity
 
FileItemSimilarity(File, long) - Constructor for class org.apache.mahout.cf.taste.impl.similarity.file.FileItemSimilarity
 
FileLineIterable - Class in org.apache.mahout.common.iterator
Iterable representing the lines of a text file.
FileLineIterable(File) - Constructor for class org.apache.mahout.common.iterator.FileLineIterable
Creates a over a given file, assuming a UTF-8 encoding.
FileLineIterable(File, boolean) - Constructor for class org.apache.mahout.common.iterator.FileLineIterable
Creates a over a given file, assuming a UTF-8 encoding.
FileLineIterable(File, Charset, boolean) - Constructor for class org.apache.mahout.common.iterator.FileLineIterable
Creates a over a given file, using the given encoding.
FileLineIterable(InputStream) - Constructor for class org.apache.mahout.common.iterator.FileLineIterable
 
FileLineIterable(InputStream, boolean) - Constructor for class org.apache.mahout.common.iterator.FileLineIterable
 
FileLineIterable(InputStream, Charset, boolean) - Constructor for class org.apache.mahout.common.iterator.FileLineIterable
 
FileLineIterator - Class in org.apache.mahout.common.iterator
Iterates over the lines of a text file.
FileLineIterator(File) - Constructor for class org.apache.mahout.common.iterator.FileLineIterator
Creates a over a given file, assuming a UTF-8 encoding.
FileLineIterator(File, boolean) - Constructor for class org.apache.mahout.common.iterator.FileLineIterator
Creates a over a given file, assuming a UTF-8 encoding.
FileLineIterator(File, Charset, boolean) - Constructor for class org.apache.mahout.common.iterator.FileLineIterator
Creates a over a given file, using the given encoding.
FileLineIterator(InputStream) - Constructor for class org.apache.mahout.common.iterator.FileLineIterator
 
FileLineIterator(InputStream, boolean) - Constructor for class org.apache.mahout.common.iterator.FileLineIterator
 
FileLineIterator(InputStream, Charset, boolean) - Constructor for class org.apache.mahout.common.iterator.FileLineIterator
 
FileParameter - Class in org.apache.mahout.common.parameters
 
FileParameter(String, String, Configuration, File, String) - Constructor for class org.apache.mahout.common.parameters.FileParameter
 
FilePersistenceStrategy - Class in org.apache.mahout.cf.taste.impl.recommender.svd
Provides a file-based persistent store.
FilePersistenceStrategy(File) - Constructor for class org.apache.mahout.cf.taste.impl.recommender.svd.FilePersistenceStrategy
 
FINAL_ITERATION_SUFFIX - Static variable in interface org.apache.mahout.clustering.Cluster
 
findClosestCanopy(Vector, Iterable<Canopy>) - Method in class org.apache.mahout.clustering.canopy.CanopyClusterer
 
findCoveringCanopy(MeanShiftCanopy, Iterable<MeanShiftCanopy>) - Static method in class org.apache.mahout.clustering.meanshift.MeanShiftCanopyClusterer
 
firstLine(String) - Method in class org.apache.mahout.classifier.sgd.CsvRecordFactory
Processes the first line of a file (which should contain the variable names).
firstLine(String) - Method in interface org.apache.mahout.classifier.sgd.RecordFactory
 
FixedRunningAverage - Class in org.apache.mahout.cf.taste.impl.common
A simple class that represents a fixed value of an average and count.
FixedRunningAverage(double, int) - Constructor for class org.apache.mahout.cf.taste.impl.common.FixedRunningAverage
 
FixedRunningAverageAndStdDev - Class in org.apache.mahout.cf.taste.impl.common
A simple class that represents a fixed value of an average, count and standard deviation.
FixedRunningAverageAndStdDev(double, double, int) - Constructor for class org.apache.mahout.cf.taste.impl.common.FixedRunningAverageAndStdDev
 
FixedSizeSamplingIterator<T> - Class in org.apache.mahout.common.iterator
Sample a fixed number of elements from an Iterator.
FixedSizeSamplingIterator(int, Iterator<T>) - Constructor for class org.apache.mahout.common.iterator.FixedSizeSamplingIterator
 
FLAG_DENSE - Static variable in class org.apache.mahout.math.VectorWritable
 
FLAG_LAX_PRECISION - Static variable in class org.apache.mahout.math.VectorWritable
 
FLAG_NAMED - Static variable in class org.apache.mahout.math.VectorWritable
 
FLAG_SEQUENTIAL - Static variable in class org.apache.mahout.math.VectorWritable
 
flush(double, Vector) - Method in class org.apache.mahout.vectorizer.encoders.TextValueEncoder
Adds all of the tokens that we counted up to a vector.
ForestVisualizer - Class in org.apache.mahout.classifier.df.tools
This tool is to visualize the Decision Forest
format(String, Analyzer, File, Charset, File) - Static method in class org.apache.mahout.classifier.BayesFileFormatter
Write the input files to the outdir, one output file per input file
formatCluster(Cluster) - Static method in class org.apache.mahout.clustering.kmeans.Cluster
Format the cluster for output
formatVector(Vector, String[]) - Static method in class org.apache.mahout.clustering.AbstractCluster
Return a human-readable formatted string representation of the vector, not intended to be complete nor usable as an input/output representation
forwardAlgorithm(HmmModel, int[], boolean) - Static method in class org.apache.mahout.classifier.sequencelearning.hmm.HmmAlgorithms
External function to compute a matrix of alpha factors
FPGrowth<A extends Comparable<? super A>> - Class in org.apache.mahout.fpm.pfpgrowth.fpgrowth
Implementation of PFGrowth Algorithm with FP-Bonsai pruning
FPGrowth() - Constructor for class org.apache.mahout.fpm.pfpgrowth.fpgrowth.FPGrowth
 
FPGROWTH - Static variable in class org.apache.mahout.fpm.pfpgrowth.PFPGrowth
 
FPGrowthDriver - Class in org.apache.mahout.fpm.pfpgrowth
 
FPGrowthIds - Class in org.apache.mahout.fpm.pfpgrowth.fpgrowth2
Implementation of PFGrowth Algorithm
FPGrowthIds() - Constructor for class org.apache.mahout.fpm.pfpgrowth.fpgrowth2.FPGrowthIds
 
FPGrowthObj<A extends Comparable<? super A>> - Class in org.apache.mahout.fpm.pfpgrowth.fpgrowth2
Implementation of PFGrowth Algorithm
FPGrowthObj() - Constructor for class org.apache.mahout.fpm.pfpgrowth.fpgrowth2.FPGrowthObj
 
FPTree - Class in org.apache.mahout.fpm.pfpgrowth.fpgrowth
The Frequent Pattern Tree datastructure used for mining patterns using FPGrowth algorithm
FPTree() - Constructor for class org.apache.mahout.fpm.pfpgrowth.fpgrowth.FPTree
 
FPTree(int) - Constructor for class org.apache.mahout.fpm.pfpgrowth.fpgrowth.FPTree
 
FPTree - Class in org.apache.mahout.fpm.pfpgrowth.fpgrowth2
A straightforward implementation of FPTrees as described in Han et.
FPTree(LongArrayList, long) - Constructor for class org.apache.mahout.fpm.pfpgrowth.fpgrowth2.FPTree
Creates an FPTree using the attribute counts in attrCountList.
FPTree(long[], long) - Constructor for class org.apache.mahout.fpm.pfpgrowth.fpgrowth2.FPTree
Creates an FPTree using the attribute counts in attrCounts.
FPTree.FPNode - Class in org.apache.mahout.fpm.pfpgrowth.fpgrowth2
 
FPTreeDepthCache - Class in org.apache.mahout.fpm.pfpgrowth.fpgrowth
Caches large FPTree Object for each level of the recursive FPGrowth algorithm to reduce allocation overhead.
FPTreeDepthCache() - Constructor for class org.apache.mahout.fpm.pfpgrowth.fpgrowth.FPTreeDepthCache
 
freeze(State<AdaptiveLogisticRegression.Wrapper, CrossFoldLearner>) - Method in class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression.Wrapper
 
Frequencies - Class in org.apache.mahout.classifier.df.tools
Compute the frequency distribution of the "class label"
This class can be used when the criterion variable is the categorical attribute.
FrequenciesJob - Class in org.apache.mahout.classifier.df.tools
Temporary class used to compute the frequency distribution of the "class attribute".
This class can be used when the criterion variable is the categorical attribute.
FrequenciesJob(Path, Path, Path) - Constructor for class org.apache.mahout.classifier.df.tools.FrequenciesJob
 
FREQUENT_PATTERNS - Static variable in class org.apache.mahout.fpm.pfpgrowth.PFPGrowth
 
FrequentPatternMaxHeap - Class in org.apache.mahout.fpm.pfpgrowth.fpgrowth
keeps top K Attributes in a TreeSet
FrequentPatternMaxHeap(int, boolean) - Constructor for class org.apache.mahout.fpm.pfpgrowth.fpgrowth.FrequentPatternMaxHeap
 
fromList(Iterable<String>) - Static method in class org.apache.mahout.vectorizer.encoders.Dictionary
 
fromRho(double, double[]) - Static method in class org.apache.mahout.math.hadoop.stochasticsvd.qr.GivensThinSolver
 
fromString(CharSequence) - Static method in class org.apache.mahout.clustering.dirichlet.models.DistributionDescription
 
fromString(String) - Static method in class org.apache.mahout.common.StringUtils
Restores the object from its string representation.
FullRunningAverage - Class in org.apache.mahout.cf.taste.impl.common
A simple class that can keep track of a running avearage of a series of numbers.
FullRunningAverage() - Constructor for class org.apache.mahout.cf.taste.impl.common.FullRunningAverage
 
FullRunningAverage(int, double) - Constructor for class org.apache.mahout.cf.taste.impl.common.FullRunningAverage
 
FullRunningAverageAndStdDev - Class in org.apache.mahout.cf.taste.impl.common
Extends FullRunningAverage to add a running standard deviation computation.
FullRunningAverageAndStdDev() - Constructor for class org.apache.mahout.cf.taste.impl.common.FullRunningAverageAndStdDev
 
FullRunningAverageAndStdDev(int, double, double, double) - Constructor for class org.apache.mahout.cf.taste.impl.common.FullRunningAverageAndStdDev
 
FullRunningAverageAndStdDevWritable - Class in org.apache.mahout.cf.taste.hadoop.slopeone
 
FullRunningAverageAndStdDevWritable(FullRunningAverageAndStdDev) - Constructor for class org.apache.mahout.cf.taste.hadoop.slopeone.FullRunningAverageAndStdDevWritable
 
FuzzyKMeansClusterer - Class in org.apache.mahout.clustering.fuzzykmeans
 
FuzzyKMeansClusterer(DistanceMeasure, double, double) - Constructor for class org.apache.mahout.clustering.fuzzykmeans.FuzzyKMeansClusterer
Init the fuzzy k-means clusterer with the distance measure to use for comparison.
FuzzyKMeansClusterer(Configuration) - Constructor for class org.apache.mahout.clustering.fuzzykmeans.FuzzyKMeansClusterer
 
FuzzyKMeansClusterer() - Constructor for class org.apache.mahout.clustering.fuzzykmeans.FuzzyKMeansClusterer
 
FuzzyKMeansClusteringPolicy - Class in org.apache.mahout.clustering
This is a probability-weighted clustering policy, suitable for fuzzy k-means clustering
FuzzyKMeansClusteringPolicy() - Constructor for class org.apache.mahout.clustering.FuzzyKMeansClusteringPolicy
 
FuzzyKMeansClusterMapper - Class in org.apache.mahout.clustering.fuzzykmeans
 
FuzzyKMeansClusterMapper() - Constructor for class org.apache.mahout.clustering.fuzzykmeans.FuzzyKMeansClusterMapper
 
FuzzyKMeansCombiner - Class in org.apache.mahout.clustering.fuzzykmeans
 
FuzzyKMeansCombiner() - Constructor for class org.apache.mahout.clustering.fuzzykmeans.FuzzyKMeansCombiner
 
FuzzyKMeansConfigKeys - Interface in org.apache.mahout.clustering.fuzzykmeans
 
FuzzyKMeansDriver - Class in org.apache.mahout.clustering.fuzzykmeans
 
FuzzyKMeansDriver() - Constructor for class org.apache.mahout.clustering.fuzzykmeans.FuzzyKMeansDriver
 
FuzzyKMeansMapper - Class in org.apache.mahout.clustering.fuzzykmeans
 
FuzzyKMeansMapper() - Constructor for class org.apache.mahout.clustering.fuzzykmeans.FuzzyKMeansMapper
 
FuzzyKMeansReducer - Class in org.apache.mahout.clustering.fuzzykmeans
 
FuzzyKMeansReducer() - Constructor for class org.apache.mahout.clustering.fuzzykmeans.FuzzyKMeansReducer
 

G

G_LIST - Static variable in class org.apache.mahout.fpm.pfpgrowth.PFPGrowth
 
GaussianAccumulator - Interface in org.apache.mahout.clustering
 
GaussianCluster - Class in org.apache.mahout.clustering.dirichlet.models
 
GaussianCluster() - Constructor for class org.apache.mahout.clustering.dirichlet.models.GaussianCluster
 
GaussianCluster(Vector, int) - Constructor for class org.apache.mahout.clustering.dirichlet.models.GaussianCluster
 
GaussianCluster(Vector, Vector, int) - Constructor for class org.apache.mahout.clustering.dirichlet.models.GaussianCluster
 
GaussianClusterDistribution - Class in org.apache.mahout.clustering.dirichlet.models
An implementation of the ModelDistribution interface suitable for testing the DirichletCluster algorithm.
GaussianClusterDistribution() - Constructor for class org.apache.mahout.clustering.dirichlet.models.GaussianClusterDistribution
 
GaussianClusterDistribution(VectorWritable) - Constructor for class org.apache.mahout.clustering.dirichlet.models.GaussianClusterDistribution
 
generateAllGrams(Path, Path, Configuration, int, int, float, int) - Static method in class org.apache.mahout.vectorizer.collocations.llr.CollocDriver
Generate all ngrams for the DictionaryVectorizer job
generateDataset(CharSequence, boolean, FileSystem, Path) - Static method in class org.apache.mahout.classifier.df.data.DataLoader
Generates the Dataset by parsing the entire data
generateDataset(CharSequence, boolean, String[]) - Static method in class org.apache.mahout.classifier.df.data.DataLoader
Generates the Dataset by parsing the entire data
generateDescriptor(CharSequence) - Static method in class org.apache.mahout.classifier.df.data.DescriptorUtils
Generates a valid descriptor string from a user-friendly representation.
for example "3 N I N N 2 C L 5 I" generates "N N N I N N C C L I I I I I".
this useful when describing datasets with a large number of attributes
generateDescriptor(Iterable<String>) - Static method in class org.apache.mahout.classifier.df.data.DescriptorUtils
Generates a valid descriptor string from a list of tokens
generateFileNameForKeyValue(WritableComparable<?>, Writable, String) - Method in class org.apache.mahout.classifier.bayes.mapreduce.common.BayesFeatureOutputFormat
 
generateFileNameForKeyValue(WritableComparable<?>, Writable, String) - Method in class org.apache.mahout.classifier.bayes.mapreduce.common.BayesTfIdfOutputFormat
 
generateFileNameForKeyValue(WritableComparable<?>, Writable, String) - Method in class org.apache.mahout.classifier.bayes.mapreduce.common.BayesWeightSummerOutputFormat
 
generateFList(Iterator<Pair<List<A>, Long>>, int) - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.FPGrowth
Generate the Feature Frequency list from the given transaction whose frequency > minSupport
generateFList(Iterator<Pair<List<A>, Long>>, int) - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth2.FPGrowthObj
Generate the Feature Frequency list from the given transaction whose frequency > minSupport
generateFList() - Method in class org.apache.mahout.fpm.pfpgrowth.TransactionTree
 
generateNGrams() - Method in class org.apache.mahout.common.nlp.NGrams
 
generateNGramsWithoutLabel() - Method in class org.apache.mahout.common.nlp.NGrams
 
generateTopKFrequentPatterns(Iterator<Pair<List<A>, Long>>, Collection<Pair<A, Long>>, long, int, Collection<A>, OutputCollector<A, List<Pair<List<A>, Long>>>, StatusUpdater) - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.FPGrowth
Generate Top K Frequent Patterns for every feature in returnableFeatures given a stream of transactions and the minimum support
generateTopKFrequentPatterns(Iterator<Pair<IntArrayList, Long>>, LongArrayList, long, int, IntArrayList, OutputCollector<Integer, List<Pair<List<Integer>, Long>>>, StatusUpdater) - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth2.FPGrowthIds
Generate Top K Frequent Patterns for every feature in returnableFeatures given a stream of transactions and the minimum support
generateTopKFrequentPatterns(Iterator<Pair<List<A>, Long>>, Collection<Pair<A, Long>>, long, int, Collection<A>, OutputCollector<A, List<Pair<List<A>, Long>>>, StatusUpdater) - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth2.FPGrowthObj
Generate Top K Frequent Patterns for every feature in returnableFeatures given a stream of transactions and the minimum support
GenericBooleanPrefDataModel - Class in org.apache.mahout.cf.taste.impl.model
A simple DataModel which uses given user data as its data source.
GenericBooleanPrefDataModel(FastByIDMap<FastIDSet>) - Constructor for class org.apache.mahout.cf.taste.impl.model.GenericBooleanPrefDataModel
Creates a new GenericDataModel from the given users (and their preferences).
GenericBooleanPrefDataModel(FastByIDMap<FastIDSet>, FastByIDMap<FastByIDMap<Long>>) - Constructor for class org.apache.mahout.cf.taste.impl.model.GenericBooleanPrefDataModel
Creates a new GenericDataModel from the given users (and their preferences).
GenericBooleanPrefDataModel(DataModel) - Constructor for class org.apache.mahout.cf.taste.impl.model.GenericBooleanPrefDataModel
Deprecated. without direct replacement. Consider GenericBooleanPrefDataModel.toDataMap(DataModel) with GenericBooleanPrefDataModel.GenericBooleanPrefDataModel(FastByIDMap)
GenericBooleanPrefItemBasedRecommender - Class in org.apache.mahout.cf.taste.impl.recommender
A variant on GenericItemBasedRecommender which is appropriate for use when no notion of preference value exists in the data.
GenericBooleanPrefItemBasedRecommender(DataModel, ItemSimilarity) - Constructor for class org.apache.mahout.cf.taste.impl.recommender.GenericBooleanPrefItemBasedRecommender
 
GenericBooleanPrefItemBasedRecommender(DataModel, ItemSimilarity, CandidateItemsStrategy, MostSimilarItemsCandidateItemsStrategy) - Constructor for class org.apache.mahout.cf.taste.impl.recommender.GenericBooleanPrefItemBasedRecommender
 
GenericBooleanPrefUserBasedRecommender - Class in org.apache.mahout.cf.taste.impl.recommender
A variant on GenericUserBasedRecommender which is appropriate for use when no notion of preference value exists in the data.
GenericBooleanPrefUserBasedRecommender(DataModel, UserNeighborhood, UserSimilarity) - Constructor for class org.apache.mahout.cf.taste.impl.recommender.GenericBooleanPrefUserBasedRecommender
 
GenericDataModel - Class in org.apache.mahout.cf.taste.impl.model
A simple DataModel which uses a given List of users as its data source.
GenericDataModel(FastByIDMap<PreferenceArray>) - Constructor for class org.apache.mahout.cf.taste.impl.model.GenericDataModel
Creates a new from the given users (and their preferences).
GenericDataModel(FastByIDMap<PreferenceArray>, FastByIDMap<FastByIDMap<Long>>) - Constructor for class org.apache.mahout.cf.taste.impl.model.GenericDataModel
Creates a new from the given users (and their preferences).
GenericDataModel(DataModel) - Constructor for class org.apache.mahout.cf.taste.impl.model.GenericDataModel
Deprecated. without direct replacement. Consider GenericDataModel.toDataMap(DataModel) with GenericDataModel.GenericDataModel(FastByIDMap)
GenericItemBasedRecommender - Class in org.apache.mahout.cf.taste.impl.recommender
A simple Recommender which uses a given DataModel and ItemSimilarity to produce recommendations.
GenericItemBasedRecommender(DataModel, ItemSimilarity, CandidateItemsStrategy, MostSimilarItemsCandidateItemsStrategy) - Constructor for class org.apache.mahout.cf.taste.impl.recommender.GenericItemBasedRecommender
 
GenericItemBasedRecommender(DataModel, ItemSimilarity) - Constructor for class org.apache.mahout.cf.taste.impl.recommender.GenericItemBasedRecommender
 
GenericItemBasedRecommender.MostSimilarEstimator - Class in org.apache.mahout.cf.taste.impl.recommender
 
GenericItemBasedRecommender.MostSimilarEstimator(long, ItemSimilarity, Rescorer<LongPair>) - Constructor for class org.apache.mahout.cf.taste.impl.recommender.GenericItemBasedRecommender.MostSimilarEstimator
 
GenericItemPreferenceArray - Class in org.apache.mahout.cf.taste.impl.model
Like GenericUserPreferenceArray but stores preferences for one item (all item IDs the same) rather than one user.
GenericItemPreferenceArray(int) - Constructor for class org.apache.mahout.cf.taste.impl.model.GenericItemPreferenceArray
 
GenericItemPreferenceArray(List<? extends Preference>) - Constructor for class org.apache.mahout.cf.taste.impl.model.GenericItemPreferenceArray
 
GenericItemSimilarity - Class in org.apache.mahout.cf.taste.impl.similarity
A "generic" GenericItemSimilarity.ItemItemSimilarity which takes a static list of precomputed item similarities and bases its responses on that alone.
GenericItemSimilarity(Iterable<GenericItemSimilarity.ItemItemSimilarity>) - Constructor for class org.apache.mahout.cf.taste.impl.similarity.GenericItemSimilarity
Creates a from a precomputed list of GenericItemSimilarity.ItemItemSimilaritys.
GenericItemSimilarity(Iterable<GenericItemSimilarity.ItemItemSimilarity>, int) - Constructor for class org.apache.mahout.cf.taste.impl.similarity.GenericItemSimilarity
Like GenericItemSimilarity.GenericItemSimilarity(Iterable), but will only keep the specified number of similarities from the given Iterable of similarities.
GenericItemSimilarity(ItemSimilarity, DataModel) - Constructor for class org.apache.mahout.cf.taste.impl.similarity.GenericItemSimilarity
Builds a list of item-item similarities given an GenericItemSimilarity.ItemItemSimilarity implementation and a DataModel, rather than a list of GenericItemSimilarity.ItemItemSimilaritys.
GenericItemSimilarity(ItemSimilarity, DataModel, int) - Constructor for class org.apache.mahout.cf.taste.impl.similarity.GenericItemSimilarity
Like GenericItemSimilarity.GenericItemSimilarity(ItemSimilarity, DataModel) )}, but will only keep the specified number of similarities from the given DataModel.
GenericItemSimilarity.ItemItemSimilarity - Class in org.apache.mahout.cf.taste.impl.similarity
Encapsulates a similarity between two items.
GenericItemSimilarity.ItemItemSimilarity(long, long, double) - Constructor for class org.apache.mahout.cf.taste.impl.similarity.GenericItemSimilarity.ItemItemSimilarity
 
GenericPreference - Class in org.apache.mahout.cf.taste.impl.model
A simple Preference encapsulating an item and preference value.
GenericPreference(long, long, float) - Constructor for class org.apache.mahout.cf.taste.impl.model.GenericPreference
 
GenericRecommendedItem - Class in org.apache.mahout.cf.taste.impl.recommender
A simple implementation of RecommendedItem.
GenericRecommendedItem(long, float) - Constructor for class org.apache.mahout.cf.taste.impl.recommender.GenericRecommendedItem
 
GenericRecommenderIRStatsEvaluator - Class in org.apache.mahout.cf.taste.impl.eval
For each user, these implementation determine the top n preferences, then evaluate the IR statistics based on a DataModel that does not have these values.
GenericRecommenderIRStatsEvaluator() - Constructor for class org.apache.mahout.cf.taste.impl.eval.GenericRecommenderIRStatsEvaluator
 
GenericRecommenderIRStatsEvaluator(RelevantItemsDataSplitter) - Constructor for class org.apache.mahout.cf.taste.impl.eval.GenericRecommenderIRStatsEvaluator
 
GenericRelevantItemsDataSplitter - Class in org.apache.mahout.cf.taste.impl.eval
Picks relevant items to be those with the strongest preference, and includes the other users' preferences in full.
GenericRelevantItemsDataSplitter() - Constructor for class org.apache.mahout.cf.taste.impl.eval.GenericRelevantItemsDataSplitter
 
GenericUserBasedRecommender - Class in org.apache.mahout.cf.taste.impl.recommender
A simple Recommender which uses a given DataModel and UserNeighborhood to produce recommendations.
GenericUserBasedRecommender(DataModel, UserNeighborhood, UserSimilarity) - Constructor for class org.apache.mahout.cf.taste.impl.recommender.GenericUserBasedRecommender
 
GenericUserPreferenceArray - Class in org.apache.mahout.cf.taste.impl.model
Like GenericItemPreferenceArray but stores preferences for one user (all user IDs the same) rather than one item.
GenericUserPreferenceArray(int) - Constructor for class org.apache.mahout.cf.taste.impl.model.GenericUserPreferenceArray
 
GenericUserPreferenceArray(List<? extends Preference>) - Constructor for class org.apache.mahout.cf.taste.impl.model.GenericUserPreferenceArray
 
GenericUserSimilarity - Class in org.apache.mahout.cf.taste.impl.similarity
 
GenericUserSimilarity(Iterable<GenericUserSimilarity.UserUserSimilarity>) - Constructor for class org.apache.mahout.cf.taste.impl.similarity.GenericUserSimilarity
 
GenericUserSimilarity(Iterable<GenericUserSimilarity.UserUserSimilarity>, int) - Constructor for class org.apache.mahout.cf.taste.impl.similarity.GenericUserSimilarity
 
GenericUserSimilarity(UserSimilarity, DataModel) - Constructor for class org.apache.mahout.cf.taste.impl.similarity.GenericUserSimilarity
 
GenericUserSimilarity(UserSimilarity, DataModel, int) - Constructor for class org.apache.mahout.cf.taste.impl.similarity.GenericUserSimilarity
 
GenericUserSimilarity.UserUserSimilarity - Class in org.apache.mahout.cf.taste.impl.similarity
 
GenericUserSimilarity.UserUserSimilarity(long, long, double) - Constructor for class org.apache.mahout.cf.taste.impl.similarity.GenericUserSimilarity.UserUserSimilarity
 
get(K) - Method in class org.apache.mahout.cf.taste.impl.common.Cache
Returns cached value for a key.
get(long) - Method in class org.apache.mahout.cf.taste.impl.common.FastByIDMap
 
get(Object) - Method in class org.apache.mahout.cf.taste.impl.common.FastMap
 
get(K) - Method in interface org.apache.mahout.cf.taste.impl.common.Retriever
 
get(int) - Method in class org.apache.mahout.cf.taste.impl.model.BooleanItemPreferenceArray
 
get(int) - Method in class org.apache.mahout.cf.taste.impl.model.BooleanUserPreferenceArray
 
get(int) - Method in class org.apache.mahout.cf.taste.impl.model.GenericItemPreferenceArray
 
get(int) - Method in class org.apache.mahout.cf.taste.impl.model.GenericUserPreferenceArray
 
get(int) - Method in interface org.apache.mahout.cf.taste.model.PreferenceArray
 
get(int) - Method in class org.apache.mahout.classifier.df.data.Data
Returns the element at the specified position
get(int) - Method in class org.apache.mahout.classifier.df.data.Instance
Return the attribute at the specified position
get() - Method in class org.apache.mahout.common.parameters.AbstractParameter
 
get(String) - Method in class org.apache.mahout.common.Parameters
 
get(String, String) - Method in class org.apache.mahout.common.Parameters
 
get() - Method in interface org.apache.mahout.common.parameters.Parameter
 
get(int) - Method in class org.apache.mahout.ep.State
Returns a transformed parameter.
get(K) - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.LeastKCache
 
get() - Method in class org.apache.mahout.math.MatrixWritable
 
get() - Method in class org.apache.mahout.math.VarIntWritable
 
get() - Method in class org.apache.mahout.math.VarLongWritable
 
get() - Method in class org.apache.mahout.math.VectorWritable
 
getAbtBlockHeight() - Method in class org.apache.mahout.math.hadoop.stochasticsvd.SSVDSolver
 
getAccuracy(String) - Method in class org.apache.mahout.classifier.ConfusionMatrix
 
getActual() - Method in class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression.TrainingExample
 
getAID() - Method in class org.apache.mahout.cf.taste.hadoop.EntityEntityWritable
 
getAllOtherItems(long, PreferenceArray) - Method in class org.apache.mahout.cf.taste.impl.recommender.AbstractRecommender
 
getAllOtherItems(long[], long) - Method in class org.apache.mahout.cf.taste.impl.recommender.GenericBooleanPrefUserBasedRecommender
 
getAllOtherItems(long[], long) - Method in class org.apache.mahout.cf.taste.impl.recommender.GenericUserBasedRecommender
 
getAnalyzerClassFromOption() - Method in class org.apache.mahout.common.AbstractJob
 
getAnalyzerClassName() - Method in class org.apache.mahout.vectorizer.VectorizerConfig
 
getAttr() - Method in class org.apache.mahout.classifier.df.split.Split
 
getAttributeAtIndex(int) - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.FPTree
 
getAucEvaluator() - Method in class org.apache.mahout.classifier.sgd.CrossFoldLearner
 
getAverage() - Method in class org.apache.mahout.cf.taste.hadoop.slopeone.FullRunningAverageAndStdDevWritable
 
getAverage() - Method in class org.apache.mahout.cf.taste.impl.common.FixedRunningAverage
 
getAverage() - Method in class org.apache.mahout.cf.taste.impl.common.FullRunningAverage
 
getAverage() - Method in class org.apache.mahout.cf.taste.impl.common.InvertedRunningAverage
 
getAverage() - Method in class org.apache.mahout.cf.taste.impl.common.InvertedRunningAverageAndStdDev
 
getAverage() - Method in interface org.apache.mahout.cf.taste.impl.common.RunningAverage
 
getAverage() - Method in class org.apache.mahout.cf.taste.impl.common.WeightedRunningAverage
 
getAverageItemPref(long) - Method in class org.apache.mahout.cf.taste.impl.recommender.slopeone.file.FileDiffStorage
 
getAverageItemPref(long) - Method in class org.apache.mahout.cf.taste.impl.recommender.slopeone.MemoryDiffStorage
 
getAverageItemPref(long) - Method in interface org.apache.mahout.cf.taste.recommender.slopeone.DiffStorage
 
getAverageStd() - Method in interface org.apache.mahout.clustering.GaussianAccumulator
 
getAverageStd() - Method in class org.apache.mahout.clustering.OnlineGaussianAccumulator
 
getAverageStd() - Method in class org.apache.mahout.clustering.RunningSumsGaussianAccumulator
 
getBaseGradient() - Method in class org.apache.mahout.classifier.sgd.RankingGradient
 
getBasePath() - Method in class org.apache.mahout.classifier.bayes.BayesParameters
 
getBaseRecordWriter(FileSystem, JobConf, String, Progressable) - Method in class org.apache.mahout.classifier.bayes.mapreduce.common.BayesFeatureOutputFormat
 
getBaseRecordWriter(FileSystem, JobConf, String, Progressable) - Method in class org.apache.mahout.classifier.bayes.mapreduce.common.BayesTfIdfOutputFormat
 
getBaseRecordWriter(FileSystem, JobConf, String, Progressable) - Method in class org.apache.mahout.classifier.bayes.mapreduce.common.BayesWeightSummerOutputFormat
 
getBasisVector(int) - Method in class org.apache.mahout.math.hadoop.decomposer.HdfsBackedLanczosState
 
getBest() - Method in class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression
 
getBeta() - Method in class org.apache.mahout.classifier.sgd.AbstractOnlineLogisticRegression
 
getBID() - Method in class org.apache.mahout.cf.taste.hadoop.EntityEntityWritable
 
getBlock() - Method in class org.apache.mahout.math.hadoop.stochasticsvd.DenseBlockWritable
 
getBottomLevelClusterPath(Path, String) - Static method in class org.apache.mahout.clustering.topdown.PathDirectory
Each cluster produced by top level clustering is processed in output/"bottomLevelCluster"/clusterId.
getBoundPoints() - Method in class org.apache.mahout.clustering.meanshift.MeanShiftCanopy
 
getBuffer() - Method in class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression
 
getBytes() - Method in class org.apache.mahout.common.IntPairWritable
 
getBytes() - Method in class org.apache.mahout.vectorizer.collocations.llr.Gram
 
getBytes() - Method in class org.apache.mahout.vectorizer.collocations.llr.GramKey
 
getCaches() - Method in class org.apache.mahout.vectorizer.encoders.CachingContinuousValueEncoder
 
getCaches() - Method in class org.apache.mahout.vectorizer.encoders.CachingStaticWordValueEncoder
 
getCandidateItems(long, PreferenceArray, DataModel) - Method in class org.apache.mahout.cf.taste.impl.recommender.AbstractCandidateItemsStrategy
 
getCandidateItems(long[], DataModel) - Method in class org.apache.mahout.cf.taste.impl.recommender.AbstractCandidateItemsStrategy
 
getCandidateItems(long, PreferenceArray, DataModel) - Method in interface org.apache.mahout.cf.taste.recommender.CandidateItemsStrategy
 
getCandidateItems(long[], DataModel) - Method in interface org.apache.mahout.cf.taste.recommender.MostSimilarItemsCandidateItemsStrategy
 
getCanopies(Configuration) - Static method in class org.apache.mahout.clustering.meanshift.MeanShiftCanopyClusterMapper
 
getCardinality() - Method in class org.apache.mahout.vectorizer.VectorizerConfig
 
getCategory(int) - Method in class org.apache.mahout.classifier.sgd.ModelDissector.Weight
 
getCenter() - Method in class org.apache.mahout.clustering.AbstractCluster
 
getCenter() - Method in interface org.apache.mahout.clustering.Cluster
Get the "center" of the Cluster as a Vector
getCenter() - Method in class org.apache.mahout.clustering.dirichlet.DirichletCluster
 
getCenters(Iterable<Canopy>) - Static method in class org.apache.mahout.clustering.canopy.CanopyClusterer
Iterate through the canopies, adding their centroids to a list
getChunkSizeInMegabytes() - Method in class org.apache.mahout.vectorizer.VectorizerConfig
 
getClassname() - Method in enum org.apache.mahout.math.hadoop.similarity.cooccurrence.measures.VectorSimilarityMeasures
 
getCleanedEigensPath() - Method in class org.apache.mahout.math.hadoop.decomposer.EigenVerificationJob
 
getCLIOption(String) - Method in class org.apache.mahout.common.AbstractJob
 
getCluster(long) - Method in class org.apache.mahout.cf.taste.impl.recommender.TreeClusteringRecommender
 
getCluster(long) - Method in class org.apache.mahout.cf.taste.impl.recommender.TreeClusteringRecommender2
 
getCluster(long) - Method in interface org.apache.mahout.cf.taste.recommender.ClusteringRecommender
Returns the cluster of users to which the given user, denoted by user ID, belongs.
getClusterOutputClusteredPoints(Path) - Static method in class org.apache.mahout.clustering.topdown.PathDirectory
The top level clustered points before post processing is generated here.
getClusterPathForClusterId(Path, String) - Static method in class org.apache.mahout.clustering.topdown.PathDirectory
Each clusters path name is its clusterId.
getClusterPostProcessorOutputDirectory(Path) - Static method in class org.apache.mahout.clustering.topdown.PathDirectory
The output of top level clusters is post processed and kept in this path.
getClusters() - Method in class org.apache.mahout.cf.taste.impl.recommender.TreeClusteringRecommender
 
getClusters() - Method in class org.apache.mahout.cf.taste.impl.recommender.TreeClusteringRecommender2
 
getClusters() - Method in interface org.apache.mahout.cf.taste.recommender.ClusteringRecommender
Returns all clusters of users.
getClusters(Configuration) - Static method in class org.apache.mahout.clustering.dirichlet.DirichletClusterMapper
 
getClusters() - Method in class org.apache.mahout.clustering.dirichlet.DirichletState
 
getCnt() - Method in class org.apache.mahout.math.hadoop.stochasticsvd.qr.GivensThinSolver
 
getCol() - Method in class org.apache.mahout.clustering.spectral.common.VertexWritable
 
getCol() - Method in class org.apache.mahout.math.hadoop.DistributedRowMatrix.MatrixEntryWritable
 
getColumn() - Method in class org.apache.mahout.clustering.spectral.eigencuts.EigencutsSensitivityNode
 
getCombinedTempPath(String, String) - Method in class org.apache.mahout.common.AbstractJob
 
getCombinerState() - Method in class org.apache.mahout.clustering.ClusterObservations
 
getCompressedTree() - Method in class org.apache.mahout.fpm.pfpgrowth.TransactionTree
 
getConditionalEntropy() - Method in class org.apache.mahout.math.stats.entropy.InformationGain
 
getConf() - Method in class org.apache.mahout.clustering.lda.cvb.InMemoryCollapsedVariationalBayes0
 
getConf() - Method in class org.apache.mahout.clustering.lda.cvb.TopicModel
 
getConf() - Method in class org.apache.mahout.math.hadoop.decomposer.DistributedLanczosSolver.DistributedLanczosSolverJob
 
getConf() - Method in class org.apache.mahout.math.hadoop.decomposer.DistributedLanczosSolver
 
getConf() - Method in class org.apache.mahout.math.hadoop.decomposer.HdfsBackedLanczosState
 
getConf() - Method in class org.apache.mahout.math.hadoop.DistributedRowMatrix
 
getConf() - Method in class org.apache.mahout.math.hadoop.solver.DistributedConjugateGradientSolver.DistributedConjugateGradientSolverJob
 
getConf() - Method in class org.apache.mahout.math.hadoop.solver.DistributedConjugateGradientSolver
 
getConf() - Method in class org.apache.mahout.vectorizer.VectorizerConfig
 
getConfusionMatrix() - Method in class org.apache.mahout.classifier.ConfusionMatrix
 
getConfusionMatrix() - Method in class org.apache.mahout.classifier.ResultAnalyzer
 
getCorrect(String) - Method in class org.apache.mahout.classifier.ConfusionMatrix
 
getCosAngleError() - Method in class org.apache.mahout.math.hadoop.decomposer.EigenVector
 
getCosAngleError(CharSequence) - Static method in class org.apache.mahout.math.hadoop.decomposer.EigenVector
 
getCount() - Method in class org.apache.mahout.cf.taste.hadoop.EntityCountWritable
 
getCount() - Method in class org.apache.mahout.cf.taste.impl.common.FixedRunningAverage
 
getCount() - Method in class org.apache.mahout.cf.taste.impl.common.FullRunningAverage
 
getCount() - Method in class org.apache.mahout.cf.taste.impl.common.InvertedRunningAverage
 
getCount() - Method in class org.apache.mahout.cf.taste.impl.common.InvertedRunningAverageAndStdDev
 
getCount() - Method in interface org.apache.mahout.cf.taste.impl.common.RunningAverage
 
getCount() - Method in class org.apache.mahout.cf.taste.impl.common.WeightedRunningAverage
 
getCount(String, String) - Method in class org.apache.mahout.classifier.ConfusionMatrix
 
getCumulativeInitialProbabilities(HmmModel) - Static method in class org.apache.mahout.classifier.sequencelearning.hmm.HmmUtils
Compute the cumulative distribution of the initial hidden state probabilities for the given HMM model.
getCumulativeOutputMatrix(HmmModel) - Static method in class org.apache.mahout.classifier.sequencelearning.hmm.HmmUtils
Compute the cumulative output probability matrix for the given HMM model.
getCumulativeTransitionMatrix(HmmModel) - Static method in class org.apache.mahout.classifier.sequencelearning.hmm.HmmUtils
Compute the cumulative transition probability matrix for the given HMM model.
getCurrentKey() - Method in class org.apache.mahout.classifier.df.mapreduce.inmem.InMemInputFormat.InMemRecordReader
 
getCurrentValue() - Method in class org.apache.mahout.classifier.df.mapreduce.inmem.InMemInputFormat.InMemRecordReader
 
getCustomJobName(String, JobContext, Class<? extends Mapper>, Class<? extends Reducer>) - Static method in class org.apache.mahout.common.HadoopUtil
 
getData() - Method in class org.apache.mahout.math.hadoop.stochasticsvd.UpperTriangular
 
getDataFile() - Method in class org.apache.mahout.cf.taste.impl.model.file.FileDataModel
 
getDataModel() - Method in class org.apache.mahout.cf.taste.impl.recommender.AbstractRecommender
 
getDataModel() - Method in class org.apache.mahout.cf.taste.impl.recommender.CachingRecommender
 
getDataModel() - Method in class org.apache.mahout.cf.taste.impl.similarity.AbstractItemSimilarity
 
getDataModel() - Method in interface org.apache.mahout.cf.taste.recommender.Recommender
 
getDataPath() - Method in class org.apache.mahout.classifier.df.mapreduce.Builder
 
getDataset() - Method in class org.apache.mahout.classifier.df.data.Data
 
getDataset() - Method in class org.apache.mahout.classifier.df.mapreduce.MapredMapper
 
getDataSource() - Method in interface org.apache.mahout.cf.taste.model.JDBCDataModel
 
getDefaultCandidateItemsStrategy() - Static method in class org.apache.mahout.cf.taste.impl.recommender.AbstractRecommender
 
getDefaultLabel() - Method in class org.apache.mahout.classifier.ConfusionMatrix
 
getDefaultMostSimilarItemsCandidateItemsStrategy() - Static method in class org.apache.mahout.cf.taste.impl.recommender.GenericItemBasedRecommender
 
getDelimiter() - Method in class org.apache.mahout.cf.taste.impl.model.file.FileDataModel
 
getDiagonalMatrix() - Method in class org.apache.mahout.math.hadoop.decomposer.HdfsBackedLanczosState
 
getDictionary() - Method in class org.apache.mahout.vectorizer.encoders.AdaptiveWordValueEncoder
 
getDiff(long, long) - Method in class org.apache.mahout.cf.taste.impl.recommender.slopeone.file.FileDiffStorage
 
getDiff(long, long) - Method in class org.apache.mahout.cf.taste.impl.recommender.slopeone.MemoryDiffStorage
 
getDiff(long, long) - Method in interface org.apache.mahout.cf.taste.recommender.slopeone.DiffStorage
 
getDiffs(long, long, PreferenceArray) - Method in class org.apache.mahout.cf.taste.impl.recommender.slopeone.file.FileDiffStorage
 
getDiffs(long, long, PreferenceArray) - Method in class org.apache.mahout.cf.taste.impl.recommender.slopeone.MemoryDiffStorage
 
getDiffs(long, long, PreferenceArray) - Method in interface org.apache.mahout.cf.taste.recommender.slopeone.DiffStorage
 
getDirichletState(Configuration) - Static method in class org.apache.mahout.clustering.dirichlet.DirichletMapper
 
getDistanceMeasure() - Method in class org.apache.mahout.clustering.dirichlet.models.DistributionDescription
 
getDistributedCacheFile(Configuration, int) - Static method in class org.apache.mahout.classifier.df.mapreduce.Builder
Helper method.
getEigenValue() - Method in class org.apache.mahout.math.hadoop.decomposer.EigenVector
 
getEigenValue(CharSequence) - Static method in class org.apache.mahout.math.hadoop.decomposer.EigenVector
 
getEmissionMatrix() - Method in class org.apache.mahout.classifier.sequencelearning.hmm.HmmModel
Getter function to get the output state probability matrix
getEncoderClass() - Method in class org.apache.mahout.vectorizer.VectorizerConfig
 
getEncoderName() - Method in class org.apache.mahout.vectorizer.VectorizerConfig
 
getEntries() - Method in class org.apache.mahout.common.IntegerTuple
Fetch the list of entries from the tuple
getEntries() - Method in class org.apache.mahout.common.IntTuple
Fetch the list of entries from the tuple
getEntries() - Method in class org.apache.mahout.common.StringTuple
Fetch the list of entries from the tuple
getEntropy() - Method in class org.apache.mahout.math.stats.entropy.InformationGain
 
getEntropy() - Method in class org.apache.mahout.math.stats.entropy.InformationGainRatio
 
getEp() - Method in class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression
 
getExponent() - Method in class org.apache.mahout.common.distance.MinkowskiDistanceMeasure
 
getF1Measure() - Method in interface org.apache.mahout.cf.taste.eval.IRStatistics
See F-measure.
getF1Measure() - Method in class org.apache.mahout.cf.taste.impl.eval.IRStatisticsImpl
 
getFallOut() - Method in interface org.apache.mahout.cf.taste.eval.IRStatistics
See Fall-Out.
getFallOut() - Method in class org.apache.mahout.cf.taste.impl.eval.IRStatisticsImpl
 
getFeature() - Method in class org.apache.mahout.classifier.sgd.ModelDissector.Weight
 
getFetchSize() - Method in class org.apache.mahout.cf.taste.impl.common.jdbc.AbstractJDBCComponent
 
getFileStatus(Path, PathType, PathFilter, Comparator<FileStatus>, Configuration) - Static method in class org.apache.mahout.common.HadoopUtil
 
getFirst() - Method in class org.apache.mahout.common.IntPairWritable
 
getFirst() - Method in class org.apache.mahout.common.LongPair
 
getFirst() - Method in class org.apache.mahout.common.Pair
 
getFirstId() - Method in class org.apache.mahout.classifier.df.mapreduce.inmem.InMemInputFormat.InMemInputSplit
 
getFirstLevelTree(Integer) - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.FPTreeDepthCache
 
getFirstTreeId() - Method in class org.apache.mahout.classifier.df.mapreduce.partial.Step1Mapper
 
getFitness(T, List<? extends T>) - Method in class org.apache.mahout.ga.watchmaker.STFitnessEvaluator
 
getFNMeasure(double) - Method in interface org.apache.mahout.cf.taste.eval.IRStatistics
See F-measure.
getFNMeasure(double) - Method in class org.apache.mahout.cf.taste.impl.eval.IRStatisticsImpl
 
getFrequency() - Method in class org.apache.mahout.common.IntPairWritable.Frequency
 
getFrequency() - Method in class org.apache.mahout.vectorizer.collocations.llr.Gram
 
getGamma() - Method in class org.apache.mahout.clustering.lda.LDAInference.InferredDocument
 
getGramSize() - Method in class org.apache.mahout.classifier.bayes.BayesParameters
 
getGroup() - Method in class org.apache.mahout.common.AbstractJob
 
getGroup(int, int) - Static method in class org.apache.mahout.fpm.pfpgrowth.PFPGrowth
 
getGroupKey() - Method in class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression.TrainingExample
 
getGroupMembers(int, int, int) - Static method in class org.apache.mahout.fpm.pfpgrowth.PFPGrowth
 
getHeaderNext(int) - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.FPTree
 
getHeaderSupportCount(int) - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.FPTree
 
getHeaderTableAttributes() - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.FPTree
 
getHeaderTableCount() - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.FPTree
 
getHeap() - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.FrequentPatternMaxHeap
 
getHiddenStateID(String) - Method in class org.apache.mahout.classifier.sequencelearning.hmm.HmmModel
Lookup the ID for the given hidden state name
getHiddenStateName(int) - Method in class org.apache.mahout.classifier.sequencelearning.hmm.HmmModel
Lookup the name for the given hidden state ID
getHiddenStateNames() - Method in class org.apache.mahout.classifier.sequencelearning.hmm.HmmModel
Getter method for the hidden state Names map
getHits() - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.FPTreeDepthCache
 
getID() - Method in class org.apache.mahout.cf.taste.hadoop.EntityCountWritable
 
getID() - Method in class org.apache.mahout.cf.taste.hadoop.EntityPrefWritable
 
getId() - Method in class org.apache.mahout.clustering.AbstractCluster
 
getId() - Method in interface org.apache.mahout.clustering.Cluster
Get the id of the Cluster
getId() - Method in class org.apache.mahout.clustering.dirichlet.DirichletCluster
 
getId() - Method in class org.apache.mahout.ep.State
 
getIdentifier() - Method in class org.apache.mahout.clustering.AbstractCluster
 
getIdentifier() - Method in class org.apache.mahout.clustering.canopy.Canopy
 
getIdentifier() - Method in class org.apache.mahout.clustering.dirichlet.models.GaussianCluster
 
getIdentifier() - Method in class org.apache.mahout.clustering.DistanceMeasureCluster
 
getIdentifier() - Method in class org.apache.mahout.clustering.fuzzykmeans.SoftCluster
 
getIdentifier() - Method in class org.apache.mahout.clustering.kmeans.Cluster
 
getIdentifier() - Method in class org.apache.mahout.clustering.meanshift.MeanShiftCanopy
 
getIdName() - Method in class org.apache.mahout.classifier.sgd.CsvRecordFactory
 
getIDs() - Method in class org.apache.mahout.cf.taste.impl.model.BooleanItemPreferenceArray
 
getIDs() - Method in class org.apache.mahout.cf.taste.impl.model.BooleanUserPreferenceArray
 
getIDs() - Method in class org.apache.mahout.cf.taste.impl.model.GenericItemPreferenceArray
 
getIDs() - Method in class org.apache.mahout.cf.taste.impl.model.GenericUserPreferenceArray
 
getIDs() - Method in interface org.apache.mahout.cf.taste.model.PreferenceArray
 
getIdString(CharSequence) - Method in class org.apache.mahout.classifier.sgd.CsvRecordFactory
Extract the id column value from the CSV record
getIg() - Method in class org.apache.mahout.classifier.df.split.Split
 
getIgnored() - Method in class org.apache.mahout.classifier.df.data.Dataset
 
getIndex() - Method in class org.apache.mahout.math.hadoop.decomposer.EigenVector
 
getIndex(CharSequence) - Static method in class org.apache.mahout.math.hadoop.decomposer.EigenVector
 
getInformationGain() - Method in class org.apache.mahout.math.stats.entropy.InformationGain
 
getInformationGain() - Method in class org.apache.mahout.math.stats.entropy.InformationGainRatio
 
getInformationGainRatio() - Method in class org.apache.mahout.math.stats.entropy.InformationGainRatio
 
getInitialProbabilities() - Method in class org.apache.mahout.classifier.sequencelearning.hmm.HmmModel
Getter function to return the vector of initial hidden state probabilities
getInitialVector(VectorIterable) - Method in class org.apache.mahout.math.hadoop.decomposer.DistributedLanczosSolver
For the distributed case, the best guess at a useful initialization state for Lanczos we'll chose to be uniform over all input dimensions, L_2 normalized.
getInputPath() - Method in class org.apache.mahout.common.AbstractJob
Returns the input path established by a call to AbstractJob.parseArguments(String[]).
getInstance() - Static method in class org.apache.mahout.cf.taste.impl.recommender.ByValueRecommendedItemComparator
 
getInstance() - Method in class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression.TrainingExample
 
getInt(String, int) - Method in class org.apache.mahout.common.Parameters
 
getInverseCovarianceMatrix() - Method in class org.apache.mahout.common.distance.MahalanobisDistanceMeasure
 
getItemFeatures(long) - Method in class org.apache.mahout.cf.taste.impl.recommender.svd.Factorization
 
getItemID(int) - Method in class org.apache.mahout.cf.taste.impl.model.BooleanItemPreferenceArray
 
getItemID() - Method in class org.apache.mahout.cf.taste.impl.model.BooleanPreference
 
getItemID(int) - Method in class org.apache.mahout.cf.taste.impl.model.BooleanUserPreferenceArray
 
getItemID(int) - Method in class org.apache.mahout.cf.taste.impl.model.GenericItemPreferenceArray
 
getItemID() - Method in class org.apache.mahout.cf.taste.impl.model.GenericPreference
 
getItemID(int) - Method in class org.apache.mahout.cf.taste.impl.model.GenericUserPreferenceArray
 
getItemID() - Method in class org.apache.mahout.cf.taste.impl.recommender.GenericRecommendedItem
 
getItemID() - Method in interface org.apache.mahout.cf.taste.model.Preference
 
getItemID(int) - Method in interface org.apache.mahout.cf.taste.model.PreferenceArray
 
getItemID() - Method in interface org.apache.mahout.cf.taste.recommender.RecommendedItem
 
getItemID1() - Method in class org.apache.mahout.cf.taste.impl.similarity.GenericItemSimilarity.ItemItemSimilarity
 
getItemID2() - Method in class org.apache.mahout.cf.taste.impl.similarity.GenericItemSimilarity.ItemItemSimilarity
 
getItemIDMappings() - Method in class org.apache.mahout.cf.taste.impl.recommender.svd.Factorization
 
getItemIDs() - Method in class org.apache.mahout.cf.taste.impl.model.file.FileDataModel
 
getItemIDs() - Method in class org.apache.mahout.cf.taste.impl.model.GenericBooleanPrefDataModel
 
getItemIDs() - Method in class org.apache.mahout.cf.taste.impl.model.GenericDataModel
 
getItemIDs() - Method in class org.apache.mahout.cf.taste.impl.model.PlusAnonymousUserDataModel
 
getItemIDs() - Method in interface org.apache.mahout.cf.taste.model.DataModel
 
getItemIDsFromUser(long) - Method in class org.apache.mahout.cf.taste.impl.model.file.FileDataModel
 
getItemIDsFromUser(long) - Method in class org.apache.mahout.cf.taste.impl.model.GenericBooleanPrefDataModel
 
getItemIDsFromUser(long) - Method in class org.apache.mahout.cf.taste.impl.model.GenericDataModel
 
getItemIDsFromUser(long) - Method in class org.apache.mahout.cf.taste.impl.model.PlusAnonymousUserDataModel
 
getItemIDsFromUser(long) - Method in interface org.apache.mahout.cf.taste.model.DataModel
 
getItemInstance() - Static method in class org.apache.mahout.cf.taste.impl.recommender.NullRescorer
 
getItemItemPairInstance() - Static method in class org.apache.mahout.cf.taste.impl.recommender.NullRescorer
 
getKey() - Method in class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression.TrainingExample
 
getKey() - Method in class org.apache.mahout.clustering.spectral.common.IntDoublePairWritable
 
getKeyClass() - Method in class org.apache.mahout.common.iterator.sequencefile.SequenceFileIterator
 
getKeys(String) - Method in interface org.apache.mahout.classifier.bayes.Datastore
get the keySet of a given Matrix/Vector as given by name
getKeys(String) - Method in class org.apache.mahout.classifier.bayes.InMemoryBayesDatastore
 
getKP() - Method in class org.apache.mahout.math.hadoop.stochasticsvd.qr.QRFirstStep
 
getLabel() - Method in class org.apache.mahout.classifier.ClassifierResult
 
getLabel(Instance) - Method in class org.apache.mahout.classifier.df.data.Dataset
 
getLabelId() - Method in class org.apache.mahout.classifier.df.data.Dataset
 
getLabels(Datastore) - Method in interface org.apache.mahout.classifier.bayes.Algorithm
Returns the labels in the given Model
getLabels() - Method in class org.apache.mahout.classifier.bayes.ClassifierContext
Gets the labels in the given model
getLabels() - Method in class org.apache.mahout.classifier.ConfusionMatrix
 
getLabels() - Method in class org.apache.mahout.math.MultiLabelVectorWritable
 
getLabelString(double) - Method in class org.apache.mahout.classifier.df.data.Dataset
Returns the label value in the data This method can be used when the criterion variable is the categorical attribute.
getLambda() - Method in class org.apache.mahout.classifier.sgd.AbstractOnlineLogisticRegression
 
getLearner() - Method in class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression.Wrapper
 
getLength() - Method in class org.apache.mahout.classifier.df.mapreduce.inmem.InMemInputFormat.InMemInputSplit
 
getLength() - Method in class org.apache.mahout.common.IntPairWritable
 
getLength() - Method in class org.apache.mahout.vectorizer.collocations.llr.Gram
 
getLength() - Method in class org.apache.mahout.vectorizer.collocations.llr.GramKey
 
getLocations() - Method in class org.apache.mahout.classifier.df.mapreduce.inmem.InMemInputFormat.InMemInputSplit
 
getLogBase() - Method in class org.apache.mahout.cf.taste.impl.transforms.InverseUserFrequency
 
getLogLikelihood() - Method in class org.apache.mahout.classifier.ClassifierResult
 
getLogLikelihood() - Method in class org.apache.mahout.classifier.sgd.CrossFoldLearner
 
getLogLikelihood() - Method in class org.apache.mahout.clustering.lda.LDAInference.InferredDocument
 
getLogLikelihood() - Method in class org.apache.mahout.clustering.lda.LDAState
 
getLogTotal(int) - Method in class org.apache.mahout.clustering.lda.LDAState
 
getM() - Method in class org.apache.mahout.clustering.fuzzykmeans.FuzzyKMeansClusterer
 
getM() - Method in class org.apache.mahout.math.hadoop.stochasticsvd.qr.GivensThinSolver
 
getMappedParams() - Method in class org.apache.mahout.ep.State
Returns all the parameters in mapped form.
getMaps() - Method in class org.apache.mahout.ep.State
 
getMass() - Method in class org.apache.mahout.clustering.meanshift.MeanShiftCanopy
 
getMatrix() - Method in class org.apache.mahout.classifier.ConfusionMatrix
 
getMaxImpact() - Method in class org.apache.mahout.classifier.sgd.ModelDissector.Weight
 
getMaxInterval() - Method in class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression
 
getMaxIters() - Method in class org.apache.mahout.clustering.lda.cvb.CachingCVB0Mapper
 
getMaxNGramSize() - Method in class org.apache.mahout.vectorizer.VectorizerConfig
 
getMaxPreference() - Method in interface org.apache.mahout.cf.taste.eval.RecommenderEvaluator
Deprecated. see DataModel.getMaxPreference()
getMaxPreference() - Method in class org.apache.mahout.cf.taste.impl.eval.AbstractDifferenceRecommenderEvaluator
 
getMaxPreference() - Method in class org.apache.mahout.cf.taste.impl.model.AbstractDataModel
 
getMaxPreference() - Method in class org.apache.mahout.cf.taste.impl.model.file.FileDataModel
 
getMaxPreference() - Method in class org.apache.mahout.cf.taste.impl.model.PlusAnonymousUserDataModel
 
getMaxPreference() - Method in interface org.apache.mahout.cf.taste.model.DataModel
 
getMaxTime() - Method in class org.apache.mahout.common.TimingStatistics
 
getMean() - Method in interface org.apache.mahout.clustering.GaussianAccumulator
 
getMean() - Method in class org.apache.mahout.clustering.OnlineGaussianAccumulator
 
getMean() - Method in class org.apache.mahout.clustering.RunningSumsGaussianAccumulator
 
getMeanTime() - Method in class org.apache.mahout.common.TimingStatistics
 
getMeanVector() - Method in class org.apache.mahout.common.distance.MahalanobisDistanceMeasure
 
getMeasure() - Method in class org.apache.mahout.clustering.dirichlet.models.DistanceMeasureClusterDistribution
 
getMeasure() - Method in class org.apache.mahout.clustering.DistanceMeasureCluster
 
getMeasure() - Method in class org.apache.mahout.clustering.fuzzykmeans.FuzzyKMeansClusterer
 
getMinDF() - Method in class org.apache.mahout.classifier.bayes.BayesParameters
 
getMinInterval() - Method in class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression
 
getMinLLRValue() - Method in class org.apache.mahout.vectorizer.VectorizerConfig
 
getMinPreference() - Method in interface org.apache.mahout.cf.taste.eval.RecommenderEvaluator
Deprecated. see DataModel.getMinPreference()
getMinPreference() - Method in class org.apache.mahout.cf.taste.impl.eval.AbstractDifferenceRecommenderEvaluator
 
getMinPreference() - Method in class org.apache.mahout.cf.taste.impl.model.AbstractDataModel
 
getMinPreference() - Method in class org.apache.mahout.cf.taste.impl.model.file.FileDataModel
 
getMinPreference() - Method in class org.apache.mahout.cf.taste.impl.model.PlusAnonymousUserDataModel
 
getMinPreference() - Method in interface org.apache.mahout.cf.taste.model.DataModel
 
getMinSupport() - Method in class org.apache.mahout.classifier.bayes.BayesParameters
 
getMinSupport() - Method in class org.apache.mahout.vectorizer.VectorizerConfig
 
getMinTime() - Method in class org.apache.mahout.common.TimingStatistics
 
getMisses() - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.FPTreeDepthCache
 
getMixture() - Method in class org.apache.mahout.clustering.dirichlet.DirichletState
 
getMk() - Method in class org.apache.mahout.cf.taste.impl.common.FullRunningAverageAndStdDev
 
getModel() - Method in class org.apache.mahout.classifier.discriminative.LinearTrainer
Retrieves the trained model if called after train, otherwise the raw model.
getModel() - Method in class org.apache.mahout.classifier.naivebayes.AbstractNaiveBayesClassifier
 
getModel() - Method in class org.apache.mahout.clustering.dirichlet.DirichletCluster
 
getModelFactory() - Method in class org.apache.mahout.clustering.dirichlet.DirichletState
 
getModelFactory() - Method in class org.apache.mahout.clustering.dirichlet.models.DistributionDescription
 
getModelPaths(Configuration) - Static method in class org.apache.mahout.clustering.lda.cvb.CVB0Driver
 
getModelPrototype() - Method in class org.apache.mahout.clustering.dirichlet.models.AbstractVectorModelDistribution
 
getModelPrototype() - Method in class org.apache.mahout.clustering.dirichlet.models.DistributionDescription
 
getModels() - Method in class org.apache.mahout.classifier.sgd.CrossFoldLearner
 
getModels() - Method in class org.apache.mahout.clustering.ClusterClassifier
 
getModels() - Method in class org.apache.mahout.clustering.dirichlet.DirichletState
 
getModelTrainer() - Method in class org.apache.mahout.clustering.lda.cvb.CachingCVB0Mapper
 
getN() - Method in interface org.apache.mahout.clustering.GaussianAccumulator
 
getN() - Method in class org.apache.mahout.clustering.OnlineGaussianAccumulator
 
getN() - Method in class org.apache.mahout.clustering.RunningSumsGaussianAccumulator
 
getN() - Method in class org.apache.mahout.math.hadoop.stochasticsvd.qr.GivensThinSolver
 
getName() - Method in class org.apache.mahout.vectorizer.encoders.FeatureVectorEncoder
 
getNbTrees(Configuration) - Static method in class org.apache.mahout.classifier.df.mapreduce.Builder
Get the number of trees for the map-reduce job.
getNbTrees() - Method in class org.apache.mahout.classifier.df.mapreduce.inmem.InMemInputFormat.InMemInputSplit
 
getNCalls() - Method in class org.apache.mahout.common.TimingStatistics
 
getNewModels() - Method in class org.apache.mahout.clustering.dirichlet.DirichletReducer
 
getNormalizedDiscountedCumulativeGain() - Method in interface org.apache.mahout.cf.taste.eval.IRStatistics
See Normalized Discounted Cumulative Gain.
getNormalizedDiscountedCumulativeGain() - Method in class org.apache.mahout.cf.taste.impl.eval.IRStatisticsImpl
 
getNormPower() - Method in class org.apache.mahout.vectorizer.VectorizerConfig
 
getNrOfHiddenStates() - Method in class org.apache.mahout.classifier.sequencelearning.hmm.HmmModel
Getter Method for the number of hidden states
getNrOfOutputStates() - Method in class org.apache.mahout.classifier.sequencelearning.hmm.HmmModel
Getter Method for the number of output states
getNumberItems() - Method in class org.apache.mahout.math.stats.entropy.Entropy
Returns the number of elements in the file.
getNumberOfClusters(Path, Configuration) - Static method in class org.apache.mahout.clustering.topdown.postprocessor.ClusterCountReader
Reads the number of clusters present by reading the clusters-*-final file.
getNumCategories() - Method in class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression
 
getNumClusters() - Method in class org.apache.mahout.clustering.dirichlet.DirichletState
 
getNumFeatures() - Method in class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression
 
getNumFeatures() - Method in class org.apache.mahout.classifier.sgd.CrossFoldLearner
 
getNumItems() - Method in class org.apache.mahout.cf.taste.impl.model.file.FileDataModel
 
getNumItems() - Method in class org.apache.mahout.cf.taste.impl.model.GenericBooleanPrefDataModel
 
getNumItems() - Method in class org.apache.mahout.cf.taste.impl.model.GenericDataModel
 
getNumItems() - Method in class org.apache.mahout.cf.taste.impl.model.PlusAnonymousUserDataModel
 
getNumItems() - Method in interface org.apache.mahout.cf.taste.model.DataModel
 
getNumMaps(Configuration) - Static method in class org.apache.mahout.classifier.df.mapreduce.Builder
Return the value of "mapred.map.tasks".
getNumNondefaultElements() - Method in class org.apache.mahout.math.hadoop.stochasticsvd.UpperTriangular
 
getNumPoints() - Method in class org.apache.mahout.clustering.AbstractCluster
 
getNumPoints() - Method in interface org.apache.mahout.clustering.Cluster
Get an integer denoting the number of points observed by this cluster
getNumPoints() - Method in class org.apache.mahout.clustering.dirichlet.DirichletCluster
 
getNumReducers() - Method in class org.apache.mahout.vectorizer.VectorizerConfig
 
getNumRows() - Method in class org.apache.mahout.math.hadoop.stochasticsvd.SparseRowBlockWritable
 
getNumTerms() - Method in class org.apache.mahout.clustering.lda.cvb.TopicModel
 
getNumTopics() - Method in class org.apache.mahout.clustering.lda.cvb.CachingCVB0Mapper
 
getNumTopics() - Method in class org.apache.mahout.clustering.lda.cvb.TopicModel
 
getNumTopics() - Method in class org.apache.mahout.clustering.lda.LDAState
 
getNumUsers() - Method in class org.apache.mahout.cf.taste.impl.model.file.FileDataModel
 
getNumUsers() - Method in class org.apache.mahout.cf.taste.impl.model.GenericBooleanPrefDataModel
 
getNumUsers() - Method in class org.apache.mahout.cf.taste.impl.model.GenericDataModel
 
getNumUsers() - Method in class org.apache.mahout.cf.taste.impl.model.PlusAnonymousUserDataModel
 
getNumUsers() - Method in interface org.apache.mahout.cf.taste.model.DataModel
 
getNumUsersWithPreferenceFor(long) - Method in class org.apache.mahout.cf.taste.impl.model.file.FileDataModel
 
getNumUsersWithPreferenceFor(long, long) - Method in class org.apache.mahout.cf.taste.impl.model.file.FileDataModel
 
getNumUsersWithPreferenceFor(long) - Method in class org.apache.mahout.cf.taste.impl.model.GenericBooleanPrefDataModel
 
getNumUsersWithPreferenceFor(long, long) - Method in class org.apache.mahout.cf.taste.impl.model.GenericBooleanPrefDataModel
 
getNumUsersWithPreferenceFor(long) - Method in class org.apache.mahout.cf.taste.impl.model.GenericDataModel
 
getNumUsersWithPreferenceFor(long, long) - Method in class org.apache.mahout.cf.taste.impl.model.GenericDataModel
 
getNumUsersWithPreferenceFor(long) - Method in class org.apache.mahout.cf.taste.impl.model.PlusAnonymousUserDataModel
 
getNumUsersWithPreferenceFor(long, long) - Method in class org.apache.mahout.cf.taste.impl.model.PlusAnonymousUserDataModel
 
getNumUsersWithPreferenceFor(long) - Method in interface org.apache.mahout.cf.taste.model.DataModel
 
getNumUsersWithPreferenceFor(long, long) - Method in interface org.apache.mahout.cf.taste.model.DataModel
 
getNumWords() - Method in class org.apache.mahout.clustering.lda.LDAState
 
getObservations() - Method in class org.apache.mahout.clustering.AbstractCluster
 
getOmni() - Method in class org.apache.mahout.ep.State
 
getOption(String) - Method in class org.apache.mahout.common.AbstractJob
 
getOption(String, String) - Method in class org.apache.mahout.common.AbstractJob
Get the option, else the default
getOuterBlockHeight() - Method in class org.apache.mahout.math.hadoop.stochasticsvd.SSVDSolver
 
getOutputPath(Configuration) - Method in class org.apache.mahout.classifier.df.mapreduce.Builder
Output Directory name
getOutputPath() - Method in class org.apache.mahout.common.AbstractJob
Returns the output path established by a call to AbstractJob.parseArguments(String[]).
getOutputPath(String) - Method in class org.apache.mahout.common.AbstractJob
 
getOutputStateID(String) - Method in class org.apache.mahout.classifier.sequencelearning.hmm.HmmModel
Lookup the ID for the given output state name
getOutputStateName(int) - Method in class org.apache.mahout.classifier.sequencelearning.hmm.HmmModel
Lookup the name for the given output state id
getOutputStateNames() - Method in class org.apache.mahout.classifier.sequencelearning.hmm.HmmModel
Getter method for the output state Names map
getOutputTempPath() - Method in class org.apache.mahout.math.hadoop.DistributedRowMatrix
 
getPair() - Method in class org.apache.mahout.common.IntPairWritable.Frequency
 
getParameters() - Method in class org.apache.mahout.classifier.sgd.CrossFoldLearner
 
getParameters() - Method in class org.apache.mahout.clustering.AbstractCluster
 
getParameters() - Method in class org.apache.mahout.clustering.dirichlet.DirichletCluster
 
getParameters() - Method in class org.apache.mahout.common.distance.ChebyshevDistanceMeasure
 
getParameters() - Method in class org.apache.mahout.common.distance.CosineDistanceMeasure
 
getParameters() - Method in class org.apache.mahout.common.distance.MahalanobisDistanceMeasure
 
getParameters() - Method in class org.apache.mahout.common.distance.ManhattanDistanceMeasure
 
getParameters() - Method in class org.apache.mahout.common.distance.MinkowskiDistanceMeasure
 
getParameters() - Method in class org.apache.mahout.common.distance.SquaredEuclideanDistanceMeasure
 
getParameters() - Method in class org.apache.mahout.common.distance.WeightedDistanceMeasure
 
getParameters() - Method in class org.apache.mahout.common.parameters.AbstractParameter
 
getParameters() - Method in class org.apache.mahout.common.parameters.CompositeParameter
 
getParameters() - Method in interface org.apache.mahout.common.parameters.Parametered
 
getParams() - Method in class org.apache.mahout.ep.State
 
getPartition(StringTuple, DoubleWritable, int) - Method in class org.apache.mahout.classifier.bayes.mapreduce.common.FeaturePartitioner
 
getPartition(GramKey, Gram, int) - Method in class org.apache.mahout.vectorizer.collocations.llr.GramKeyPartitioner
 
getPattern() - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.Pattern
 
getPatterns() - Method in class org.apache.mahout.fpm.pfpgrowth.convertors.string.TopKStringPatterns
 
getPayload() - Method in class org.apache.mahout.ep.State
 
getPopulation() - Method in class org.apache.mahout.ep.EvolutionaryProcess
 
getPopulationSize() - Method in class org.apache.mahout.ep.EvolutionaryProcess
 
getPostProcessedClusterDirectories() - Method in class org.apache.mahout.clustering.topdown.postprocessor.ClusterOutputPostProcessor
 
getPrecision() - Method in interface org.apache.mahout.cf.taste.eval.IRStatistics
See Precision.
getPrecision() - Method in class org.apache.mahout.cf.taste.impl.eval.IRStatisticsImpl
 
getPredictors() - Method in class org.apache.mahout.classifier.sgd.CsvRecordFactory
Returns a list of the names of the predictor variables.
getPredictors() - Method in interface org.apache.mahout.classifier.sgd.RecordFactory
 
getPreferencesForItem(long) - Method in class org.apache.mahout.cf.taste.impl.model.file.FileDataModel
 
getPreferencesForItem(long) - Method in class org.apache.mahout.cf.taste.impl.model.GenericBooleanPrefDataModel
 
getPreferencesForItem(long) - Method in class org.apache.mahout.cf.taste.impl.model.GenericDataModel
 
getPreferencesForItem(long) - Method in class org.apache.mahout.cf.taste.impl.model.PlusAnonymousUserDataModel
 
getPreferencesForItem(long) - Method in interface org.apache.mahout.cf.taste.model.DataModel
 
getPreferencesFromUser(long) - Method in class org.apache.mahout.cf.taste.impl.model.file.FileDataModel
 
getPreferencesFromUser(long) - Method in class org.apache.mahout.cf.taste.impl.model.GenericBooleanPrefDataModel
 
getPreferencesFromUser(long) - Method in class org.apache.mahout.cf.taste.impl.model.GenericDataModel
 
getPreferencesFromUser(long) - Method in class org.apache.mahout.cf.taste.impl.model.PlusAnonymousUserDataModel
 
getPreferencesFromUser(long) - Method in interface org.apache.mahout.cf.taste.model.DataModel
 
getPreferenceTime(long, long) - Method in class org.apache.mahout.cf.taste.impl.model.file.FileDataModel
 
getPreferenceTime(long, long) - Method in class org.apache.mahout.cf.taste.impl.model.GenericBooleanPrefDataModel
 
getPreferenceTime(long, long) - Method in class org.apache.mahout.cf.taste.impl.model.GenericDataModel
 
getPreferenceTime(long, long) - Method in class org.apache.mahout.cf.taste.impl.model.PlusAnonymousUserDataModel
 
getPreferenceTime(long, long) - Method in interface org.apache.mahout.cf.taste.model.DataModel
Retrieves the time at which a preference value from a user and item was set, if known.
getPreferenceValue(long, long) - Method in class org.apache.mahout.cf.taste.impl.model.file.FileDataModel
 
getPreferenceValue(long, long) - Method in class org.apache.mahout.cf.taste.impl.model.GenericBooleanPrefDataModel
 
getPreferenceValue(long, long) - Method in class org.apache.mahout.cf.taste.impl.model.GenericDataModel
 
getPreferenceValue(long, long) - Method in class org.apache.mahout.cf.taste.impl.model.PlusAnonymousUserDataModel
 
getPreferenceValue(long, long) - Method in interface org.apache.mahout.cf.taste.model.DataModel
Retrieves the preference value for a single user and item.
getPrefs() - Method in class org.apache.mahout.cf.taste.hadoop.EntityPrefWritableArrayWritable
 
getPrefValue() - Method in class org.apache.mahout.cf.taste.hadoop.EntityPrefWritable
 
getPrefValue() - Method in class org.apache.mahout.cf.taste.hadoop.item.PrefAndSimilarityColumnWritable
 
getPrimaryLength() - Method in class org.apache.mahout.vectorizer.collocations.llr.GramKey
 
getPrimaryString() - Method in class org.apache.mahout.vectorizer.collocations.llr.GramKey
 
getPrior() - Method in class org.apache.mahout.classifier.sgd.AbstractOnlineLogisticRegression
 
getPrior() - Method in class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression
 
getPrior() - Method in class org.apache.mahout.classifier.sgd.CrossFoldLearner
 
getProbes() - Method in class org.apache.mahout.vectorizer.encoders.FeatureVectorEncoder
 
getProgress() - Method in class org.apache.mahout.classifier.df.mapreduce.inmem.InMemInputFormat.InMemRecordReader
 
getProperties() - Method in class org.apache.mahout.clustering.WeightedPropertyVectorWritable
 
getPrototypeSize() - Method in class org.apache.mahout.clustering.dirichlet.models.DistributionDescription
 
getQ() - Method in class org.apache.mahout.math.hadoop.stochasticsvd.SSVDSolver
 
getQuick(int, int) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.Omega
Get omega element at (x,y) uniformly distributed within [-1...1)
getQuick(int, int) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.UpperTriangular
 
getRadius() - Method in class org.apache.mahout.clustering.AbstractCluster
 
getRadius() - Method in interface org.apache.mahout.clustering.Cluster
Get the "radius" of the Cluster as a Vector.
getRadius() - Method in class org.apache.mahout.clustering.dirichlet.DirichletCluster
 
getRandomSeed(Configuration) - Static method in class org.apache.mahout.classifier.df.mapreduce.Builder
Returns the random seed
getRawItemData() - Method in class org.apache.mahout.cf.taste.impl.model.GenericBooleanPrefDataModel
This is used mostly internally to the framework, and shouldn't be relied upon otherwise.
getRawItemData() - Method in class org.apache.mahout.cf.taste.impl.model.GenericDataModel
This is used mostly internally to the framework, and shouldn't be relied upon otherwise.
getRawUserData() - Method in class org.apache.mahout.cf.taste.impl.model.GenericBooleanPrefDataModel
This is used mostly internally to the framework, and shouldn't be relied upon otherwise.
getRawUserData() - Method in class org.apache.mahout.cf.taste.impl.model.GenericDataModel
This is used mostly internally to the framework, and shouldn't be relied upon otherwise.
getReach() - Method in interface org.apache.mahout.cf.taste.eval.IRStatistics
 
getReach() - Method in class org.apache.mahout.cf.taste.impl.eval.IRStatisticsImpl
 
getReadModel() - Method in class org.apache.mahout.clustering.lda.cvb.ModelTrainer
 
getRecall() - Method in interface org.apache.mahout.cf.taste.eval.IRStatistics
See Recall.
getRecall() - Method in class org.apache.mahout.cf.taste.impl.eval.IRStatisticsImpl
 
getRecommendableItemIDs(long) - Method in class org.apache.mahout.cf.taste.impl.recommender.slopeone.file.FileDiffStorage
 
getRecommendableItemIDs(long) - Method in class org.apache.mahout.cf.taste.impl.recommender.slopeone.MemoryDiffStorage
 
getRecommendableItemIDs(long) - Method in interface org.apache.mahout.cf.taste.recommender.slopeone.DiffStorage
 
getRecommendedItems() - Method in class org.apache.mahout.cf.taste.hadoop.RecommendedItemsWritable
 
getRecord() - Method in class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression
 
getRecord() - Method in class org.apache.mahout.classifier.sgd.CrossFoldLearner
 
getRelevantItemsIDs(long, int, double, DataModel) - Method in interface org.apache.mahout.cf.taste.eval.RelevantItemsDataSplitter
During testing, relevant items are removed from a particular users' preferences, and a model is build using this user's other preferences and all other users.
getRelevantItemsIDs(long, int, double, DataModel) - Method in class org.apache.mahout.cf.taste.impl.eval.GenericRelevantItemsDataSplitter
 
getResults() - Method in class org.apache.mahout.classifier.df.mapreduce.Classifier
 
getRightSingularVector(int) - Method in class org.apache.mahout.math.hadoop.decomposer.HdfsBackedLanczosState
 
getRow() - Method in class org.apache.mahout.clustering.spectral.common.VertexWritable
 
getRow() - Method in class org.apache.mahout.clustering.spectral.eigencuts.EigencutsSensitivityNode
 
getRow() - Method in class org.apache.mahout.math.hadoop.DistributedRowMatrix.MatrixEntryWritable
 
getRowIndices() - Method in class org.apache.mahout.math.hadoop.stochasticsvd.SparseRowBlockWritable
 
getRowPath() - Method in class org.apache.mahout.math.hadoop.DistributedRowMatrix
 
getRows() - Method in class org.apache.mahout.math.hadoop.stochasticsvd.SparseRowBlockWritable
 
getRTilde() - Method in class org.apache.mahout.math.hadoop.stochasticsvd.qr.GivensThinSolver
 
getS0() - Method in class org.apache.mahout.clustering.AbstractCluster
 
getS0() - Method in class org.apache.mahout.clustering.ClusterObservations
 
getS1() - Method in class org.apache.mahout.clustering.AbstractCluster
 
getS1() - Method in class org.apache.mahout.clustering.ClusterObservations
 
getS2() - Method in class org.apache.mahout.clustering.AbstractCluster
 
getS2() - Method in class org.apache.mahout.clustering.ClusterObservations
 
getScaleFactor() - Method in class org.apache.mahout.math.hadoop.decomposer.HdfsBackedLanczosState
 
getScore() - Method in class org.apache.mahout.classifier.ClassifierResult
 
getScoreForLabelFeature(int, int) - Method in class org.apache.mahout.classifier.naivebayes.AbstractNaiveBayesClassifier
 
getScoreForLabelFeature(int, int) - Method in class org.apache.mahout.classifier.naivebayes.ComplementaryNaiveBayesClassifier
 
getScoreForLabelFeature(int, int) - Method in class org.apache.mahout.classifier.naivebayes.StandardNaiveBayesClassifier
 
getScoreForLabelInstance(int, Vector) - Method in class org.apache.mahout.classifier.naivebayes.AbstractNaiveBayesClassifier
 
getSecond() - Method in class org.apache.mahout.common.IntPairWritable
 
getSecond() - Method in class org.apache.mahout.common.LongPair
 
getSecond() - Method in class org.apache.mahout.common.Pair
 
getSeed() - Method in class org.apache.mahout.classifier.df.mapreduce.Builder
 
getSeed() - Method in class org.apache.mahout.classifier.df.mapreduce.inmem.InMemInputFormat.InMemInputSplit
 
getSeed() - Method in class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression
 
getSeed() - Method in class org.apache.mahout.vectorizer.encoders.CachingValueEncoder
 
getSeed() - Method in class org.apache.mahout.vectorizer.encoders.ConstantValueEncoder
 
getSeed() - Method in class org.apache.mahout.vectorizer.encoders.ContinuousValueEncoder
 
getSensitivity() - Method in class org.apache.mahout.clustering.spectral.eigencuts.EigencutsSensitivityNode
 
getSimilarity(FastIDSet, FastIDSet) - Method in interface org.apache.mahout.cf.taste.impl.recommender.ClusterSimilarity
 
getSimilarity(FastIDSet, FastIDSet) - Method in class org.apache.mahout.cf.taste.impl.recommender.FarthestNeighborClusterSimilarity
 
getSimilarity() - Method in class org.apache.mahout.cf.taste.impl.recommender.GenericItemBasedRecommender
 
getSimilarity() - Method in class org.apache.mahout.cf.taste.impl.recommender.GenericUserBasedRecommender
 
getSimilarity(FastIDSet, FastIDSet) - Method in class org.apache.mahout.cf.taste.impl.recommender.NearestNeighborClusterSimilarity
 
getSimilarityColumn() - Method in class org.apache.mahout.cf.taste.hadoop.item.PrefAndSimilarityColumnWritable
 
getSingularValues() - Method in class org.apache.mahout.math.hadoop.stochasticsvd.SSVDSolver
This contains k+p singular values resulted from the solver run.
getSingularValues() - Method in class org.apache.mahout.math.ssvd.SequentialOutOfCoreSvd
 
getSk() - Method in class org.apache.mahout.cf.taste.impl.common.FullRunningAverageAndStdDev
 
getSplit() - Method in class org.apache.mahout.classifier.df.split.Split
 
getSplits(JobContext) - Method in class org.apache.mahout.classifier.df.mapreduce.inmem.InMemInputFormat
 
getSplits(Configuration, int) - Method in class org.apache.mahout.classifier.df.mapreduce.inmem.InMemInputFormat
 
getStandardDeviation() - Method in class org.apache.mahout.cf.taste.impl.common.FixedRunningAverageAndStdDev
 
getStandardDeviation() - Method in class org.apache.mahout.cf.taste.impl.common.FullRunningAverageAndStdDev
 
getStandardDeviation() - Method in class org.apache.mahout.cf.taste.impl.common.InvertedRunningAverageAndStdDev
 
getStandardDeviation() - Method in interface org.apache.mahout.cf.taste.impl.common.RunningAverageAndStdDev
 
getStandardDeviation() - Method in class org.apache.mahout.cf.taste.impl.common.WeightedRunningAverageAndStdDev
 
getStd() - Method in interface org.apache.mahout.clustering.GaussianAccumulator
 
getStd() - Method in class org.apache.mahout.clustering.OnlineGaussianAccumulator
 
getStd() - Method in class org.apache.mahout.clustering.RunningSumsGaussianAccumulator
 
getStdDevTime() - Method in class org.apache.mahout.common.TimingStatistics
 
getStep() - Method in class org.apache.mahout.classifier.sgd.AbstractOnlineLogisticRegression
 
getStep() - Method in class org.apache.mahout.ep.State
 
getString() - Method in class org.apache.mahout.classifier.df.node.CategoricalNode
 
getString() - Method in class org.apache.mahout.classifier.df.node.Leaf
 
getString() - Method in class org.apache.mahout.classifier.df.node.Node
 
getString() - Method in class org.apache.mahout.classifier.df.node.NumericalNode
 
getString() - Method in class org.apache.mahout.vectorizer.collocations.llr.Gram
 
getStringValue() - Method in class org.apache.mahout.common.parameters.AbstractParameter
 
getStringValue() - Method in class org.apache.mahout.common.parameters.ClassParameter
 
getStringValue() - Method in class org.apache.mahout.common.parameters.CompositeParameter
 
getStringValue() - Method in class org.apache.mahout.common.parameters.FileParameter
 
getStringValue() - Method in interface org.apache.mahout.common.parameters.Parameter
 
getStringValue() - Method in class org.apache.mahout.common.parameters.StringParameter
 
getSum() - Method in class org.apache.mahout.math.hadoop.stats.VarianceTotals
 
getSumOfSquares() - Method in class org.apache.mahout.math.hadoop.stats.VarianceTotals
 
getSumSquaredTime() - Method in class org.apache.mahout.common.TimingStatistics
 
getSumTime() - Method in class org.apache.mahout.common.TimingStatistics
 
getT1() - Method in class org.apache.mahout.clustering.canopy.CanopyClusterer
 
getT1() - Method in class org.apache.mahout.clustering.meanshift.MeanShiftCanopyClusterer
 
getT2() - Method in class org.apache.mahout.clustering.canopy.CanopyClusterer
 
getT2() - Method in class org.apache.mahout.clustering.meanshift.MeanShiftCanopyClusterer
 
getT3() - Method in class org.apache.mahout.clustering.canopy.CanopyClusterer
 
getT4() - Method in class org.apache.mahout.clustering.canopy.CanopyClusterer
 
getTargetCategories() - Method in class org.apache.mahout.classifier.sgd.CsvRecordFactory
 
getTargetCategories() - Method in interface org.apache.mahout.classifier.sgd.RecordFactory
 
getTargetLabel(int) - Method in class org.apache.mahout.classifier.sgd.CsvRecordFactory
Extract the corresponding raw target label according to a code
getTargetString(CharSequence) - Method in class org.apache.mahout.classifier.sgd.CsvRecordFactory
Extract the raw target string from a line read from a CSV file.
getTaskId() - Method in class org.apache.mahout.math.hadoop.stochasticsvd.SplitPartitionedWritable
 
getTaskItemOrdinal() - Method in class org.apache.mahout.math.hadoop.stochasticsvd.SplitPartitionedWritable
 
getTempPath() - Method in class org.apache.mahout.common.AbstractJob
 
getTempPath(String) - Method in class org.apache.mahout.common.AbstractJob
 
getTfDirName() - Method in class org.apache.mahout.vectorizer.VectorizerConfig
 
getThinQtTilde() - Method in class org.apache.mahout.math.hadoop.stochasticsvd.qr.GivensThinSolver
 
getThreadCount() - Method in class org.apache.mahout.ep.EvolutionaryProcess
 
getTiming() - Method in class org.apache.mahout.cf.taste.impl.eval.LoadStatistics
 
getTopicSmoothing() - Method in class org.apache.mahout.clustering.lda.LDAState
 
getTopItemItemSimilarities(int, Iterator<GenericItemSimilarity.ItemItemSimilarity>) - Static method in class org.apache.mahout.cf.taste.impl.recommender.TopItems
Thanks to tsmorton for suggesting this functionality and writing part of the code.
getTopItems(int, LongPrimitiveIterator, IDRescorer, TopItems.Estimator<Long>) - Static method in class org.apache.mahout.cf.taste.impl.recommender.TopItems
 
getTopLevelClusterPath(Path) - Static method in class org.apache.mahout.clustering.topdown.PathDirectory
All output of top level clustering is stored in output directory/topLevelCluster.
getTopUsers(int, LongPrimitiveIterator, IDRescorer, TopItems.Estimator<Long>) - Static method in class org.apache.mahout.cf.taste.impl.recommender.TopItems
 
getTopUserUserSimilarities(int, Iterator<GenericUserSimilarity.UserUserSimilarity>) - Static method in class org.apache.mahout.cf.taste.impl.recommender.TopItems
 
getTotal(String) - Method in class org.apache.mahout.classifier.ConfusionMatrix
 
getTotalCount() - Method in class org.apache.mahout.clustering.dirichlet.DirichletCluster
 
getTotalCount() - Method in class org.apache.mahout.math.hadoop.stats.VarianceTotals
 
getTotalWeight() - Method in class org.apache.mahout.cf.taste.impl.common.WeightedRunningAverage
 
getTraceDictionary() - Method in class org.apache.mahout.classifier.sgd.CsvRecordFactory
 
getTraceDictionary() - Method in interface org.apache.mahout.classifier.sgd.RecordFactory
 
getTransformedValue(Preference) - Method in class org.apache.mahout.cf.taste.impl.transforms.InverseUserFrequency
 
getTransformedValue(Preference) - Method in class org.apache.mahout.cf.taste.impl.transforms.ZScore
 
getTransformedValue(Preference) - Method in interface org.apache.mahout.cf.taste.transforms.PreferenceTransform
 
getTransitionMatrix() - Method in class org.apache.mahout.classifier.sequencelearning.hmm.HmmModel
Getter function to get the hidden state transition matrix
getTree() - Method in class org.apache.mahout.classifier.df.mapreduce.MapredOutput
 
getTree(int) - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.FPTreeDepthCache
 
getTreeBuilder() - Method in class org.apache.mahout.classifier.df.mapreduce.Builder
 
getTreeBuilder(Configuration) - Static method in class org.apache.mahout.classifier.df.mapreduce.Builder
 
getTreeBuilder() - Method in class org.apache.mahout.classifier.df.mapreduce.MapredMapper
 
getType() - Method in class org.apache.mahout.classifier.df.node.CategoricalNode
 
getType() - Method in class org.apache.mahout.classifier.df.node.Leaf
 
getType() - Method in class org.apache.mahout.classifier.df.node.Node
 
getType() - Method in class org.apache.mahout.classifier.df.node.NumericalNode
 
getType() - Method in class org.apache.mahout.clustering.spectral.common.VertexWritable
 
getType() - Method in class org.apache.mahout.vectorizer.collocations.llr.Gram
 
getType() - Method in class org.apache.mahout.vectorizer.collocations.llr.GramKey
 
getUPath() - Method in class org.apache.mahout.math.hadoop.stochasticsvd.SSVDSolver
returns U path (if computation were requested and successful).
getUserFeatures(long) - Method in class org.apache.mahout.cf.taste.impl.recommender.svd.Factorization
 
getUserID() - Method in class org.apache.mahout.cf.taste.hadoop.item.VectorOrPrefWritable
 
getUserID(int) - Method in class org.apache.mahout.cf.taste.impl.model.BooleanItemPreferenceArray
 
getUserID() - Method in class org.apache.mahout.cf.taste.impl.model.BooleanPreference
 
getUserID(int) - Method in class org.apache.mahout.cf.taste.impl.model.BooleanUserPreferenceArray
 
getUserID(int) - Method in class org.apache.mahout.cf.taste.impl.model.GenericItemPreferenceArray
 
getUserID() - Method in class org.apache.mahout.cf.taste.impl.model.GenericPreference
 
getUserID(int) - Method in class org.apache.mahout.cf.taste.impl.model.GenericUserPreferenceArray
 
getUserID() - Method in interface org.apache.mahout.cf.taste.model.Preference
 
getUserID(int) - Method in interface org.apache.mahout.cf.taste.model.PreferenceArray
 
getUserID1() - Method in class org.apache.mahout.cf.taste.impl.similarity.GenericUserSimilarity.UserUserSimilarity
 
getUserID2() - Method in class org.apache.mahout.cf.taste.impl.similarity.GenericUserSimilarity.UserUserSimilarity
 
getUserIDMappings() - Method in class org.apache.mahout.cf.taste.impl.recommender.svd.Factorization
 
getUserIDs() - Method in class org.apache.mahout.cf.taste.hadoop.item.VectorAndPrefsWritable
 
getUserIDs() - Method in class org.apache.mahout.cf.taste.impl.model.file.FileDataModel
 
getUserIDs() - Method in class org.apache.mahout.cf.taste.impl.model.GenericBooleanPrefDataModel
 
getUserIDs() - Method in class org.apache.mahout.cf.taste.impl.model.GenericDataModel
 
getUserIDs() - Method in class org.apache.mahout.cf.taste.impl.model.PlusAnonymousUserDataModel
 
getUserIDs() - Method in interface org.apache.mahout.cf.taste.model.DataModel
 
getUserInstance() - Static method in class org.apache.mahout.cf.taste.impl.recommender.NullRescorer
 
getUserNeighborhood(long) - Method in class org.apache.mahout.cf.taste.impl.neighborhood.CachingUserNeighborhood
 
getUserNeighborhood(long) - Method in class org.apache.mahout.cf.taste.impl.neighborhood.NearestNUserNeighborhood
 
getUserNeighborhood(long) - Method in class org.apache.mahout.cf.taste.impl.neighborhood.ThresholdUserNeighborhood
 
getUserNeighborhood(long) - Method in interface org.apache.mahout.cf.taste.neighborhood.UserNeighborhood
 
getUserUserPairInstance() - Static method in class org.apache.mahout.cf.taste.impl.recommender.NullRescorer
 
getVal() - Method in class org.apache.mahout.math.hadoop.DistributedRowMatrix.MatrixEntryWritable
 
getValue() - Method in class org.apache.mahout.cf.taste.hadoop.item.VectorOrPrefWritable
 
getValue(int) - Method in class org.apache.mahout.cf.taste.impl.model.BooleanItemPreferenceArray
 
getValue() - Method in class org.apache.mahout.cf.taste.impl.model.BooleanPreference
 
getValue(int) - Method in class org.apache.mahout.cf.taste.impl.model.BooleanUserPreferenceArray
 
getValue(int) - Method in class org.apache.mahout.cf.taste.impl.model.GenericItemPreferenceArray
 
getValue() - Method in class org.apache.mahout.cf.taste.impl.model.GenericPreference
 
getValue(int) - Method in class org.apache.mahout.cf.taste.impl.model.GenericUserPreferenceArray
 
getValue() - Method in class org.apache.mahout.cf.taste.impl.recommender.GenericRecommendedItem
 
getValue() - Method in class org.apache.mahout.cf.taste.impl.similarity.GenericItemSimilarity.ItemItemSimilarity
 
getValue() - Method in class org.apache.mahout.cf.taste.impl.similarity.GenericUserSimilarity.UserUserSimilarity
 
getValue() - Method in interface org.apache.mahout.cf.taste.model.Preference
 
getValue(int) - Method in interface org.apache.mahout.cf.taste.model.PreferenceArray
 
getValue() - Method in interface org.apache.mahout.cf.taste.recommender.RecommendedItem
A value expressing the strength of the preference for the recommended item.
getValue() - Method in class org.apache.mahout.clustering.spectral.common.IntDoublePairWritable
 
getValue() - Method in class org.apache.mahout.clustering.spectral.common.VertexWritable
 
getValue() - Method in class org.apache.mahout.ep.State
 
getValueClass() - Method in class org.apache.mahout.common.iterator.sequencefile.SequenceFileIterator
 
getValueClass() - Method in class org.apache.mahout.common.iterator.sequencefile.SequenceFileValueIterator
 
getValues() - Method in class org.apache.mahout.cf.taste.hadoop.item.VectorAndPrefsWritable
 
getVariance() - Method in interface org.apache.mahout.clustering.GaussianAccumulator
 
getVariance() - Method in class org.apache.mahout.clustering.OnlineGaussianAccumulator
 
getVariance() - Method in class org.apache.mahout.clustering.RunningSumsGaussianAccumulator
 
getVector() - Method in class org.apache.mahout.cf.taste.hadoop.item.VectorAndPrefsWritable
 
getVector() - Method in class org.apache.mahout.cf.taste.hadoop.item.VectorOrPrefWritable
 
getVector() - Method in class org.apache.mahout.clustering.WeightedVectorWritable
 
getVector() - Method in class org.apache.mahout.math.MultiLabelVectorWritable
 
getVPath() - Method in class org.apache.mahout.math.hadoop.stochasticsvd.SSVDSolver
return V path ( if computation was requested and successful ) .
getWeight(String, String, String) - Method in interface org.apache.mahout.classifier.bayes.Datastore
Gets a double value from the Matrix pointed to by the matrixName from its cell pointed to by the row and column string
getWeight(String, String) - Method in interface org.apache.mahout.classifier.bayes.Datastore
Gets a double value from the Vector pointed to by the vectorName from its cell pointed to by the index
getWeight(String, String, String) - Method in class org.apache.mahout.classifier.bayes.InMemoryBayesDatastore
 
getWeight(String, String) - Method in class org.apache.mahout.classifier.bayes.InMemoryBayesDatastore
 
getWeight() - Method in class org.apache.mahout.classifier.sgd.ModelDissector.Weight
 
getWeight(int) - Method in class org.apache.mahout.classifier.sgd.ModelDissector.Weight
 
getWeight() - Method in class org.apache.mahout.clustering.WeightedVectorWritable
 
getWeight(byte[], double) - Method in class org.apache.mahout.vectorizer.encoders.AdaptiveWordValueEncoder
 
getWeight(byte[], double) - Method in class org.apache.mahout.vectorizer.encoders.ConstantValueEncoder
 
getWeight(byte[], double) - Method in class org.apache.mahout.vectorizer.encoders.ContinuousValueEncoder
 
getWeight(byte[], double) - Method in class org.apache.mahout.vectorizer.encoders.FeatureVectorEncoder
 
getWeight(byte[], byte[], double) - Method in class org.apache.mahout.vectorizer.encoders.InteractionValueEncoder
 
getWeight(byte[], double) - Method in class org.apache.mahout.vectorizer.encoders.WordValueEncoder
 
getWeights() - Method in class org.apache.mahout.common.distance.WeightedDistanceMeasure
 
getWordCounts() - Method in class org.apache.mahout.clustering.lda.LDAInference.InferredDocument
 
givens(double, double, double[]) - Static method in class org.apache.mahout.math.hadoop.stochasticsvd.qr.GivensThinSolver
 
GivensThinSolver - Class in org.apache.mahout.math.hadoop.stochasticsvd.qr
Givens Thin solver.
GivensThinSolver(int, int) - Constructor for class org.apache.mahout.math.hadoop.stochasticsvd.qr.GivensThinSolver
 
GlobalOnlineAuc - Class in org.apache.mahout.math.stats
Computes a running estimate of AUC (see http://en.wikipedia.org/wiki/Receiver_operating_characteristic).
GlobalOnlineAuc() - Constructor for class org.apache.mahout.math.stats.GlobalOnlineAuc
 
Gradient - Interface in org.apache.mahout.classifier.sgd
Provides the ability to inject a gradient into the SGD logistic regresion.
GradientMachine - Class in org.apache.mahout.classifier.sgd
Online gradient machine learner that tries to minimize the label ranking hinge loss.
GradientMachine(int, int, int) - Constructor for class org.apache.mahout.classifier.sgd.GradientMachine
 
Gram - Class in org.apache.mahout.vectorizer.collocations.llr
Writable for holding data generated from the collocation discovery jobs.
Gram() - Constructor for class org.apache.mahout.vectorizer.collocations.llr.Gram
 
Gram(Gram) - Constructor for class org.apache.mahout.vectorizer.collocations.llr.Gram
Copy constructor
Gram(String, Gram.Type) - Constructor for class org.apache.mahout.vectorizer.collocations.llr.Gram
Create an gram with a frequency of 1
Gram(String, int, Gram.Type) - Constructor for class org.apache.mahout.vectorizer.collocations.llr.Gram
Create a gram with the specified frequency.
Gram.Type - Enum in org.apache.mahout.vectorizer.collocations.llr
 
GramKey - Class in org.apache.mahout.vectorizer.collocations.llr
A GramKey, based on the identity fields of Gram (type, string) plus a byte[] used for secondary ordering
GramKey() - Constructor for class org.apache.mahout.vectorizer.collocations.llr.GramKey
 
GramKey(Gram, byte[]) - Constructor for class org.apache.mahout.vectorizer.collocations.llr.GramKey
create a GramKey based on the specified Gram and order
GramKeyPartitioner - Class in org.apache.mahout.vectorizer.collocations.llr
Partition GramKeys based on their Gram, ignoring the secondary sort key so that all GramKeys with the same gram are sent to the same partition.
GramKeyPartitioner() - Constructor for class org.apache.mahout.vectorizer.collocations.llr.GramKeyPartitioner
 
GramSchmidt - Class in org.apache.mahout.math.hadoop.stochasticsvd.qr
Gram Schmidt quick helper.
greaterOrEquals(int, double) - Static method in class org.apache.mahout.classifier.df.data.conditions.Condition
Condition that checks if the given attribute has a value "greater or equal" than the given value
GreaterOrEquals - Class in org.apache.mahout.classifier.df.data.conditions
True if a given attribute has a value "greater or equal" than a given value
GreaterOrEquals(int, double) - Constructor for class org.apache.mahout.classifier.df.data.conditions.GreaterOrEquals
 
greatestSmall() - Method in class org.apache.mahout.cf.taste.common.MinK
 
GroupAndCountByKeyAndValueMapper - Class in org.apache.mahout.math.stats.entropy
Groups the input by key and value.
GroupAndCountByKeyAndValueMapper() - Constructor for class org.apache.mahout.math.stats.entropy.GroupAndCountByKeyAndValueMapper
 
GroupedOnlineAuc - Class in org.apache.mahout.math.stats
Implements a variant on AUC where the result returned is an average of several AUC measurements made on sub-groups of the overall data.
GroupedOnlineAuc() - Constructor for class org.apache.mahout.math.stats.GroupedOnlineAuc
 

H

HadoopUtil - Class in org.apache.mahout.common
 
hash(String) - Method in class org.apache.mahout.cf.taste.impl.model.AbstractIDMigrator
 
hash(byte[]) - Method in interface org.apache.mahout.clustering.minhash.HashFunction
 
hash(String, int, int) - Method in class org.apache.mahout.vectorizer.encoders.FeatureVectorEncoder
Hash a string and an integer into the range [0..numFeatures-1].
hash(byte[], int, int) - Static method in class org.apache.mahout.vectorizer.encoders.FeatureVectorEncoder
Hash a byte array and an integer into the range [0..numFeatures-1].
hash(String, String, int, int) - Static method in class org.apache.mahout.vectorizer.encoders.FeatureVectorEncoder
Hash two strings and an integer into the range [0..numFeatures-1].
hash(byte[], byte[], int, int) - Method in class org.apache.mahout.vectorizer.encoders.FeatureVectorEncoder
Hash two byte arrays and an integer into the range [0..numFeatures-1].
hash(String, String, String, String, int, int) - Method in class org.apache.mahout.vectorizer.encoders.FeatureVectorEncoder
Hash four strings and an integer into the range [0..numFeatures-1].
HASH_TYPE - Static variable in class org.apache.mahout.common.commandline.MinhashOptionCreator
 
hashCode() - Method in class org.apache.mahout.cf.taste.hadoop.EntityCountWritable
 
hashCode() - Method in class org.apache.mahout.cf.taste.hadoop.EntityEntityWritable
 
hashCode() - Method in class org.apache.mahout.cf.taste.hadoop.EntityPrefWritable
 
hashCode() - Method in class org.apache.mahout.cf.taste.hadoop.item.PrefAndSimilarityColumnWritable
 
hashCode() - Method in class org.apache.mahout.cf.taste.impl.common.FastByIDMap
 
hashCode() - Method in class org.apache.mahout.cf.taste.impl.common.FastIDSet
 
hashCode() - Method in class org.apache.mahout.cf.taste.impl.common.FastMap
 
hashCode() - Method in class org.apache.mahout.cf.taste.impl.model.BooleanItemPreferenceArray
 
hashCode() - Method in class org.apache.mahout.cf.taste.impl.model.BooleanUserPreferenceArray
 
hashCode() - Method in class org.apache.mahout.cf.taste.impl.model.GenericItemPreferenceArray
 
hashCode() - Method in class org.apache.mahout.cf.taste.impl.model.GenericUserPreferenceArray
 
hashCode() - Method in class org.apache.mahout.cf.taste.impl.recommender.GenericRecommendedItem
 
hashCode() - Method in class org.apache.mahout.cf.taste.impl.recommender.SimilarUser
 
hashCode() - Method in class org.apache.mahout.cf.taste.impl.recommender.svd.Factorization
 
hashCode() - Method in class org.apache.mahout.cf.taste.impl.similarity.GenericItemSimilarity.ItemItemSimilarity
 
hashCode() - Method in class org.apache.mahout.cf.taste.impl.similarity.GenericUserSimilarity.UserUserSimilarity
 
hashCode() - Method in class org.apache.mahout.classifier.df.data.Data
 
hashCode() - Method in class org.apache.mahout.classifier.df.data.Dataset
 
hashCode() - Method in class org.apache.mahout.classifier.df.data.Instance
 
hashCode() - Method in class org.apache.mahout.classifier.df.DecisionForest
 
hashCode() - Method in class org.apache.mahout.classifier.df.mapreduce.inmem.InMemInputFormat.InMemInputSplit
 
hashCode() - Method in class org.apache.mahout.classifier.df.mapreduce.MapredOutput
 
hashCode() - Method in class org.apache.mahout.classifier.df.node.CategoricalNode
 
hashCode() - Method in class org.apache.mahout.classifier.df.node.Leaf
 
hashCode() - Method in class org.apache.mahout.classifier.df.node.NumericalNode
 
hashCode() - Method in class org.apache.mahout.classifier.sgd.ModelDissector.Weight
 
hashCode() - Method in class org.apache.mahout.common.IntegerTuple
 
hashCode() - Method in class org.apache.mahout.common.IntPairWritable.Frequency
 
hashCode() - Method in class org.apache.mahout.common.IntPairWritable
 
hashCode() - Method in class org.apache.mahout.common.IntTuple
 
hashCode() - Method in class org.apache.mahout.common.LongPair
 
hashCode() - Method in class org.apache.mahout.common.Pair
 
hashCode() - Method in class org.apache.mahout.common.StringTuple
 
hashCode() - Method in class org.apache.mahout.ep.State
 
hashCode() - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.Pattern
 
hashCode() - Method in class org.apache.mahout.math.hadoop.DistributedRowMatrix.MatrixEntryWritable
 
hashCode() - Method in class org.apache.mahout.math.hadoop.stochasticsvd.SplitPartitionedWritable
 
hashCode() - Method in class org.apache.mahout.math.VarIntWritable
 
hashCode() - Method in class org.apache.mahout.math.VarLongWritable
 
hashCode() - Method in class org.apache.mahout.math.VectorWritable
 
hashesForProbe(byte[], int, String, int) - Method in class org.apache.mahout.vectorizer.encoders.FeatureVectorEncoder
Returns all of the hashes for this probe.
hashesForProbe(byte[], int, String, int) - Method in class org.apache.mahout.vectorizer.encoders.TextValueEncoder
 
HashFactory - Class in org.apache.mahout.clustering.minhash
 
HashFactory.HashType - Enum in org.apache.mahout.clustering.minhash
 
hashForProbe(String, int, String, int) - Method in class org.apache.mahout.vectorizer.encoders.CachingContinuousValueEncoder
 
hashForProbe(String, int, String, int) - Method in class org.apache.mahout.vectorizer.encoders.CachingStaticWordValueEncoder
 
hashForProbe(byte[], int, String, int) - Method in class org.apache.mahout.vectorizer.encoders.CachingValueEncoder
 
hashForProbe(byte[], int, String, int) - Method in class org.apache.mahout.vectorizer.encoders.FeatureVectorEncoder
Provides the unique hash for a particular probe.
hashForProbe(byte[], int, String, int) - Method in class org.apache.mahout.vectorizer.encoders.InteractionValueEncoder
 
hashForProbe(byte[], int, String, int) - Method in class org.apache.mahout.vectorizer.encoders.StaticWordValueEncoder
 
hashForProbe(byte[], int, String, int) - Method in class org.apache.mahout.vectorizer.encoders.TextValueEncoder
 
hashForProbe(byte[], int, String, int) - Method in class org.apache.mahout.vectorizer.encoders.WordValueEncoder
 
HashFunction - Interface in org.apache.mahout.clustering.minhash
 
hashTypeOption() - Static method in class org.apache.mahout.common.commandline.MinhashOptionCreator
Returns a default command line option for specifying the type of hash to use in MinHash clustering: Should one out of ("linear","polynomial","murmur")
hasNext() - Method in class org.apache.mahout.cf.taste.impl.common.LongPrimitiveArrayIterator
 
hasNext() - Method in class org.apache.mahout.cf.taste.impl.common.SamplingLongPrimitiveIterator
 
hasNext() - Method in class org.apache.mahout.math.hadoop.stochasticsvd.qr.QRLastStep
 
hasOption(String) - Method in class org.apache.mahout.common.AbstractJob
 
hasPreferenceValues() - Method in class org.apache.mahout.cf.taste.impl.model.file.FileDataModel
 
hasPreferenceValues() - Method in class org.apache.mahout.cf.taste.impl.model.GenericBooleanPrefDataModel
 
hasPreferenceValues() - Method in class org.apache.mahout.cf.taste.impl.model.GenericDataModel
 
hasPreferenceValues() - Method in class org.apache.mahout.cf.taste.impl.model.PlusAnonymousUserDataModel
 
hasPreferenceValues() - Method in interface org.apache.mahout.cf.taste.model.DataModel
 
hasPrefWithItemID(long) - Method in class org.apache.mahout.cf.taste.impl.model.BooleanItemPreferenceArray
 
hasPrefWithItemID(long) - Method in class org.apache.mahout.cf.taste.impl.model.BooleanUserPreferenceArray
 
hasPrefWithItemID(long) - Method in class org.apache.mahout.cf.taste.impl.model.GenericItemPreferenceArray
 
hasPrefWithItemID(long) - Method in class org.apache.mahout.cf.taste.impl.model.GenericUserPreferenceArray
 
hasPrefWithItemID(long) - Method in interface org.apache.mahout.cf.taste.model.PreferenceArray
 
hasPrefWithUserID(long) - Method in class org.apache.mahout.cf.taste.impl.model.BooleanItemPreferenceArray
 
hasPrefWithUserID(long) - Method in class org.apache.mahout.cf.taste.impl.model.BooleanUserPreferenceArray
 
hasPrefWithUserID(long) - Method in class org.apache.mahout.cf.taste.impl.model.GenericItemPreferenceArray
 
hasPrefWithUserID(long) - Method in class org.apache.mahout.cf.taste.impl.model.GenericUserPreferenceArray
 
hasPrefWithUserID(long) - Method in interface org.apache.mahout.cf.taste.model.PreferenceArray
 
HBASE_COLUMN_FAMILY - Static variable in class org.apache.mahout.classifier.bayes.mapreduce.common.BayesConstants
 
HBASE_COUNTS_ROW - Static variable in class org.apache.mahout.classifier.bayes.mapreduce.common.BayesConstants
 
HdfsBackedLanczosState - Class in org.apache.mahout.math.hadoop.decomposer
 
HdfsBackedLanczosState(VectorIterable, int, Vector, Path) - Constructor for class org.apache.mahout.math.hadoop.decomposer.HdfsBackedLanczosState
 
headerCount(int) - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth2.FPTree
Returns the count of the given attribute, as supplied on construction.
help(Parametered) - Static method in class org.apache.mahout.common.parameters.Parametered.ParameteredGeneralizations
 
helpOption() - Static method in class org.apache.mahout.common.commandline.DefaultOptionCreator
Returns a default command line option for help.
hiddenToOutput(Vector) - Method in class org.apache.mahout.classifier.sgd.GradientMachine
Feeds forward from hidden to output
HighDFWordsPruner - Class in org.apache.mahout.vectorizer
 
HISTORY - Static variable in class org.apache.mahout.math.stats.GlobalOnlineAuc
 
HmmAlgorithms - Class in org.apache.mahout.classifier.sequencelearning.hmm
Class containing implementations of the three major HMM algorithms: forward, backward and Viterbi
HmmEvaluator - Class in org.apache.mahout.classifier.sequencelearning.hmm
The HMMEvaluator class offers several methods to evaluate an HMM Model.
HmmModel - Class in org.apache.mahout.classifier.sequencelearning.hmm
Main class defining a Hidden Markov Model
HmmModel(int, int, long) - Constructor for class org.apache.mahout.classifier.sequencelearning.hmm.HmmModel
Construct a valid random Hidden-Markov parameter set with the given number of hidden and output states using a given seed.
HmmModel(int, int) - Constructor for class org.apache.mahout.classifier.sequencelearning.hmm.HmmModel
Construct a valid random Hidden-Markov parameter set with the given number of hidden and output states.
HmmModel(Matrix, Matrix, Vector) - Constructor for class org.apache.mahout.classifier.sequencelearning.hmm.HmmModel
Generates a Hidden Markov model using the specified parameters
HmmTrainer - Class in org.apache.mahout.classifier.sequencelearning.hmm
Class containing several algorithms used to train a Hidden Markov Model.
HmmUtils - Class in org.apache.mahout.classifier.sequencelearning.hmm
A collection of utilities for handling HMMModel objects.

I

identicalLabel() - Method in class org.apache.mahout.classifier.df.data.Data
checks if all the vectors have identical label values
identity() - Static method in class org.apache.mahout.ep.Mapping
Maps results to themselves.
IDMigrator - Interface in org.apache.mahout.cf.taste.model
Mahout 0.2 changed the framework to operate only in terms of numeric (long) ID values for users and items.
IDRescorer - Interface in org.apache.mahout.cf.taste.recommender
A Rescorer which operates on long primitive IDs, rather than arbitrary Objects.
idToIndex(long) - Static method in class org.apache.mahout.cf.taste.hadoop.TasteHadoopUtils
Maps a long to an int
IgSplit - Class in org.apache.mahout.classifier.df.split
Computes the best split using the Information Gain measure
IgSplit() - Constructor for class org.apache.mahout.classifier.df.split.IgSplit
 
IKernelProfile - Interface in org.apache.mahout.common.kernel
 
importEvaluations(FileSystem, Configuration, Path, Collection<Double>) - Static method in class org.apache.mahout.ga.watchmaker.OutputUtils
Reads back the evaluations.
includeBiasTerm(boolean) - Method in class org.apache.mahout.classifier.sgd.CsvRecordFactory
 
includeBiasTerm(boolean) - Method in interface org.apache.mahout.classifier.sgd.RecordFactory
 
incrementCombinerState() - Method in class org.apache.mahout.clustering.ClusterObservations
 
incrementCount(String, String, int) - Method in class org.apache.mahout.classifier.ConfusionMatrix
 
incrementCount(String, String) - Method in class org.apache.mahout.classifier.ConfusionMatrix
 
incrementFrequency(int) - Method in class org.apache.mahout.vectorizer.collocations.llr.Gram
 
incrementItemOrdinal() - Method in class org.apache.mahout.math.hadoop.stochasticsvd.SplitPartitionedWritable
 
incrementToken() - Method in class org.apache.mahout.common.lucene.IteratorTokenStream
 
IndexInstancesMapper - Class in org.apache.mahout.classifier.naivebayes.training
 
IndexInstancesMapper() - Constructor for class org.apache.mahout.classifier.naivebayes.training.IndexInstancesMapper
 
IndexInstancesMapper.Counter - Enum in org.apache.mahout.classifier.naivebayes.training
 
infer(Vector, Vector) - Method in class org.apache.mahout.clustering.lda.cvb.TopicModel
 
infer(Vector) - Method in class org.apache.mahout.clustering.lda.LDAInference
Performs inference on the given document, returning an InferredDocument.
inferPreference(long, long) - Method in class org.apache.mahout.cf.taste.impl.similarity.AveragingPreferenceInferrer
 
inferPreference(long, long) - Method in interface org.apache.mahout.cf.taste.similarity.PreferenceInferrer
Infers the given user's preference value for an item.
InformationGain - Class in org.apache.mahout.math.stats.entropy
Calculates the information gain for a SequenceFile.
InformationGain() - Constructor for class org.apache.mahout.math.stats.entropy.InformationGain
 
InformationGainRatio - Class in org.apache.mahout.math.stats.entropy
A job to calculate the normalized information gain.
InformationGainRatio() - Constructor for class org.apache.mahout.math.stats.entropy.InformationGainRatio
 
INITIAL_CLUSTERS_DIR - Static variable in interface org.apache.mahout.clustering.Cluster
 
initialCanopy(Vector, int, DistanceMeasure) - Static method in class org.apache.mahout.clustering.meanshift.MeanShiftCanopy
Create an initial Canopy, retaining the original type of the given point (e.g.
initialize(Iterable<String>) - Method in class org.apache.mahout.cf.taste.impl.model.AbstractJDBCIDMigrator
 
initialize(Iterable<String>) - Method in class org.apache.mahout.cf.taste.impl.model.MemoryIDMigrator
 
initialize(Iterable<String>) - Method in interface org.apache.mahout.cf.taste.model.UpdatableIDMigrator
Make the mapping aware of the given string IDs.
initialize(Datastore) - Method in interface org.apache.mahout.classifier.bayes.Algorithm
Initialize the data store and verifies the data in it.
initialize() - Method in class org.apache.mahout.classifier.bayes.ClassifierContext
Initializes the Context.
initialize() - Method in interface org.apache.mahout.classifier.bayes.Datastore
Initializes the and loads the model into memory/cache if necessary
initialize() - Method in class org.apache.mahout.classifier.bayes.InMemoryBayesDatastore
 
initialize(InputSplit, TaskAttemptContext) - Method in class org.apache.mahout.classifier.df.mapreduce.inmem.InMemInputFormat.InMemRecordReader
 
initWeights(Random) - Method in class org.apache.mahout.classifier.sgd.GradientMachine
Initialize weights.
InMemBuilder - Class in org.apache.mahout.classifier.df.mapreduce.inmem
MapReduce implementation where each mapper loads a full copy of the data in-memory.
InMemBuilder(TreeBuilder, Path, Path, Long, Configuration) - Constructor for class org.apache.mahout.classifier.df.mapreduce.inmem.InMemBuilder
 
InMemBuilder(TreeBuilder, Path, Path) - Constructor for class org.apache.mahout.classifier.df.mapreduce.inmem.InMemBuilder
 
InMemInputFormat - Class in org.apache.mahout.classifier.df.mapreduce.inmem
Custom InputFormat that generates InputSplits given the desired number of trees.
each input split contains a subset of the trees.
The number of splits is equal to the number of requested splits
InMemInputFormat() - Constructor for class org.apache.mahout.classifier.df.mapreduce.inmem.InMemInputFormat
 
InMemInputFormat.InMemInputSplit - Class in org.apache.mahout.classifier.df.mapreduce.inmem
Custom InputSplit that indicates how many trees are built by each mapper
InMemInputFormat.InMemInputSplit() - Constructor for class org.apache.mahout.classifier.df.mapreduce.inmem.InMemInputFormat.InMemInputSplit
 
InMemInputFormat.InMemInputSplit(int, int, Long) - Constructor for class org.apache.mahout.classifier.df.mapreduce.inmem.InMemInputFormat.InMemInputSplit
 
InMemInputFormat.InMemRecordReader - Class in org.apache.mahout.classifier.df.mapreduce.inmem
 
InMemInputFormat.InMemRecordReader(InMemInputFormat.InMemInputSplit) - Constructor for class org.apache.mahout.classifier.df.mapreduce.inmem.InMemInputFormat.InMemRecordReader
 
InMemMapper - Class in org.apache.mahout.classifier.df.mapreduce.inmem
In-memory mapper that grows the trees using a full copy of the data loaded in-memory.
InMemMapper() - Constructor for class org.apache.mahout.classifier.df.mapreduce.inmem.InMemMapper
 
InMemoryBayesDatastore - Class in org.apache.mahout.classifier.bayes
Class implementing the Datastore for Algorithms to read In-Memory model
InMemoryBayesDatastore(BayesParameters) - Constructor for class org.apache.mahout.classifier.bayes.InMemoryBayesDatastore
 
InMemoryCollapsedVariationalBayes0 - Class in org.apache.mahout.clustering.lda.cvb
Runs the same algorithm as CVB0Driver, but sequentially, in memory.
InMemoryCollapsedVariationalBayes0(Matrix, String[], int, double, double) - Constructor for class org.apache.mahout.clustering.lda.cvb.InMemoryCollapsedVariationalBayes0
 
InMemoryCollapsedVariationalBayes0(Matrix, String[], int, double, double, int, int, double, long) - Constructor for class org.apache.mahout.clustering.lda.cvb.InMemoryCollapsedVariationalBayes0
 
INPUT - Static variable in class org.apache.mahout.fpm.pfpgrowth.PFPGrowth
 
INPUT_IS_CANOPIES_OPTION - Static variable in class org.apache.mahout.clustering.meanshift.MeanShiftCanopyDriver
 
INPUT_OPTION - Static variable in class org.apache.mahout.common.commandline.DefaultOptionCreator
 
INPUT_VECTOR - Static variable in class org.apache.mahout.math.hadoop.TimesSquaredJob
 
inputIsCanopiesOption() - Static method in class org.apache.mahout.common.commandline.DefaultOptionCreator
 
inputOption() - Static method in class org.apache.mahout.common.commandline.DefaultOptionCreator
Returns a default command line option for input directory specification.
inputToHidden(Vector) - Method in class org.apache.mahout.classifier.sgd.GradientMachine
Feeds forward from input to hidden unit..
insert(Pattern) - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.FrequentPatternMaxHeap
 
Instance - Class in org.apache.mahout.classifier.df.data
Represents one data instance.
Instance(Vector) - Constructor for class org.apache.mahout.classifier.df.data.Instance
 
instantiateAs(String, Class<T>) - Static method in class org.apache.mahout.common.ClassUtils
 
instantiateAs(String, Class<T>, Class<?>[], Object[]) - Static method in class org.apache.mahout.common.ClassUtils
 
instantiateAs(Class<? extends T>, Class<T>, Class<?>[], Object[]) - Static method in class org.apache.mahout.common.ClassUtils
 
instantiateAs(Class<? extends T>, Class<T>) - Static method in class org.apache.mahout.common.ClassUtils
 
IntDoublePairWritable - Class in org.apache.mahout.clustering.spectral.common
This class is a Writable implementation of the mahout.common.Pair generic class.
IntDoublePairWritable() - Constructor for class org.apache.mahout.clustering.spectral.common.IntDoublePairWritable
 
IntDoublePairWritable(int, double) - Constructor for class org.apache.mahout.clustering.spectral.common.IntDoublePairWritable
 
integerAt(int) - Method in class org.apache.mahout.common.IntegerTuple
Fetches the string at the given location
IntegerParameter - Class in org.apache.mahout.common.parameters
 
IntegerParameter(String, String, Configuration, int, String) - Constructor for class org.apache.mahout.common.parameters.IntegerParameter
 
IntegerStringOutputConverter - Class in org.apache.mahout.fpm.pfpgrowth.convertors.integer
Collects the Patterns with Integer id and Long support and converts them to Pattern of Strings based on a reverse feature lookup map.
IntegerStringOutputConverter(OutputCollector<Text, TopKStringPatterns>, List<String>) - Constructor for class org.apache.mahout.fpm.pfpgrowth.convertors.integer.IntegerStringOutputConverter
 
IntegerTuple - Class in org.apache.mahout.common
An Ordered List of Integers which can be used in a Hadoop Map/Reduce Job
IntegerTuple() - Constructor for class org.apache.mahout.common.IntegerTuple
 
IntegerTuple(Integer) - Constructor for class org.apache.mahout.common.IntegerTuple
 
IntegerTuple(Iterable<Integer>) - Constructor for class org.apache.mahout.common.IntegerTuple
 
IntegerTuple(Integer[]) - Constructor for class org.apache.mahout.common.IntegerTuple
 
InteractionValueEncoder - Class in org.apache.mahout.vectorizer.encoders
 
InteractionValueEncoder(String, FeatureVectorEncoder, FeatureVectorEncoder) - Constructor for class org.apache.mahout.vectorizer.encoders.InteractionValueEncoder
 
intern(String) - Method in class org.apache.mahout.vectorizer.encoders.Dictionary
 
intersectionSize(FastIDSet) - Method in class org.apache.mahout.cf.taste.impl.common.FastIDSet
Convenience method to quickly compute just the size of the intersection with another .
IntPairWritable - Class in org.apache.mahout.common
A WritableComparable which encapsulates an ordered pair of signed integers.
IntPairWritable() - Constructor for class org.apache.mahout.common.IntPairWritable
 
IntPairWritable(IntPairWritable) - Constructor for class org.apache.mahout.common.IntPairWritable
 
IntPairWritable(int, int) - Constructor for class org.apache.mahout.common.IntPairWritable
 
IntPairWritable.Comparator - Class in org.apache.mahout.common
 
IntPairWritable.Comparator() - Constructor for class org.apache.mahout.common.IntPairWritable.Comparator
 
IntPairWritable.FirstGroupingComparator - Class in org.apache.mahout.common
Compare only the first part of the pair, so that reduce is called once for each value of the first part.
IntPairWritable.FirstGroupingComparator() - Constructor for class org.apache.mahout.common.IntPairWritable.FirstGroupingComparator
 
IntPairWritable.Frequency - Class in org.apache.mahout.common
A wrapper class that associates pairs with frequency (Occurences)
IntPairWritable.Frequency(IntPairWritable, double) - Constructor for class org.apache.mahout.common.IntPairWritable.Frequency
 
IntTuple - Class in org.apache.mahout.common
An Ordered List of Integers which can be used in a Hadoop Map/Reduce Job
IntTuple() - Constructor for class org.apache.mahout.common.IntTuple
 
IntTuple(int) - Constructor for class org.apache.mahout.common.IntTuple
 
IntTuple(Iterable<Integer>) - Constructor for class org.apache.mahout.common.IntTuple
 
IntTuple(int[]) - Constructor for class org.apache.mahout.common.IntTuple
 
InvalidDatastoreException - Exception in org.apache.mahout.classifier.bayes
Exception thrown when illegal access is done on the datastore or when the backend storage goes down.
InvalidDatastoreException() - Constructor for exception org.apache.mahout.classifier.bayes.InvalidDatastoreException
 
InvalidDatastoreException(String) - Constructor for exception org.apache.mahout.classifier.bayes.InvalidDatastoreException
 
InvalidDatastoreException(String, Throwable) - Constructor for exception org.apache.mahout.classifier.bayes.InvalidDatastoreException
 
InvalidDatastoreException(Throwable) - Constructor for exception org.apache.mahout.classifier.bayes.InvalidDatastoreException
 
inverse() - Method in class org.apache.mahout.cf.taste.impl.common.FixedRunningAverage
 
inverse() - Method in class org.apache.mahout.cf.taste.impl.common.FixedRunningAverageAndStdDev
 
inverse() - Method in class org.apache.mahout.cf.taste.impl.common.FullRunningAverage
 
inverse() - Method in class org.apache.mahout.cf.taste.impl.common.FullRunningAverageAndStdDev
 
inverse() - Method in class org.apache.mahout.cf.taste.impl.common.InvertedRunningAverage
 
inverse() - Method in class org.apache.mahout.cf.taste.impl.common.InvertedRunningAverageAndStdDev
 
inverse() - Method in interface org.apache.mahout.cf.taste.impl.common.RunningAverage
 
inverse() - Method in interface org.apache.mahout.cf.taste.impl.common.RunningAverageAndStdDev
 
inverse() - Method in class org.apache.mahout.cf.taste.impl.common.WeightedRunningAverage
 
inverse() - Method in class org.apache.mahout.cf.taste.impl.common.WeightedRunningAverageAndStdDev
 
InverseUserFrequency - Class in org.apache.mahout.cf.taste.impl.transforms
Implements an "inverse user frequency" transformation, which boosts preference values for items for which few users have expressed a preference, and reduces preference values for items for which many users have expressed a preference.
InverseUserFrequency(DataModel, double) - Constructor for class org.apache.mahout.cf.taste.impl.transforms.InverseUserFrequency
Creates a transformation.
invertDictionary(OpenObjectIntHashMap<String>) - Static method in class org.apache.mahout.math.MatrixUtils
 
InvertedRunningAverage - Class in org.apache.mahout.cf.taste.impl.common
 
InvertedRunningAverage(RunningAverage) - Constructor for class org.apache.mahout.cf.taste.impl.common.InvertedRunningAverage
 
InvertedRunningAverageAndStdDev - Class in org.apache.mahout.cf.taste.impl.common
 
InvertedRunningAverageAndStdDev(RunningAverageAndStdDev) - Constructor for class org.apache.mahout.cf.taste.impl.common.InvertedRunningAverageAndStdDev
 
IOUtils - Class in org.apache.mahout.common
I/O-related utility methods that don't have a better home.
IOUtils.DeleteFileOnClose - Class in org.apache.mahout.common
for temporary files, a file may be considered as a Closeable too, where file is wiped on close and thus the disk resource is released ('closed').
IOUtils.DeleteFileOnClose(File) - Constructor for class org.apache.mahout.common.IOUtils.DeleteFileOnClose
 
IOUtils.MultipleOutputsCloseableAdapter - Class in org.apache.mahout.common
MultipleOutputs to closeable adapter.
IOUtils.MultipleOutputsCloseableAdapter(MultipleOutputs) - Constructor for class org.apache.mahout.common.IOUtils.MultipleOutputsCloseableAdapter
 
IRStatistics - Interface in org.apache.mahout.cf.taste.eval
Implementations encapsulate information retrieval-related statistics about a Recommender's recommendations.
IRStatisticsImpl - Class in org.apache.mahout.cf.taste.impl.eval
 
IS_SPARSE_OUTPUT - Static variable in class org.apache.mahout.math.hadoop.TimesSquaredJob
 
isBroadcast() - Method in class org.apache.mahout.math.hadoop.stochasticsvd.SSVDSolver
 
isCategorical() - Method in enum org.apache.mahout.classifier.df.data.Dataset.Attribute
 
isConverged() - Method in class org.apache.mahout.clustering.AbstractCluster
 
isConverged() - Method in interface org.apache.mahout.clustering.Cluster
 
isConverged() - Method in class org.apache.mahout.clustering.dirichlet.DirichletCluster
 
isConverged() - Method in class org.apache.mahout.clustering.kmeans.Cluster
 
isEmpty() - Method in class org.apache.mahout.cf.taste.impl.common.FastByIDMap
 
isEmpty() - Method in class org.apache.mahout.cf.taste.impl.common.FastIDSet
 
isEmpty() - Method in class org.apache.mahout.cf.taste.impl.common.FastMap
 
isEmpty() - Method in class org.apache.mahout.classifier.df.data.Data
 
isEmpty() - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.FPTree
 
isFiltered(T) - Method in class org.apache.mahout.cf.taste.impl.recommender.NullRescorer
 
isFiltered(long) - Method in class org.apache.mahout.cf.taste.impl.recommender.NullRescorer
 
isFiltered(long) - Method in interface org.apache.mahout.cf.taste.recommender.IDRescorer
Returns true to exclude the given thing.
isFiltered(T) - Method in interface org.apache.mahout.cf.taste.recommender.Rescorer
Returns true to exclude the given thing.
isFull() - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.FrequentPatternMaxHeap
 
isFull() - Method in class org.apache.mahout.math.hadoop.stochasticsvd.qr.GivensThinSolver
 
isIdentical() - Method in class org.apache.mahout.classifier.df.data.Data
checks if all the vectors have identical attribute values
isIgnored() - Method in enum org.apache.mahout.classifier.df.data.Dataset.Attribute
 
isLabel() - Method in enum org.apache.mahout.classifier.df.data.Dataset.Attribute
 
isLogNormalize() - Method in class org.apache.mahout.vectorizer.VectorizerConfig
 
isNamedVectors() - Method in class org.apache.mahout.vectorizer.VectorizerConfig
 
isNatural() - Method in class org.apache.mahout.ga.watchmaker.MahoutFitnessEvaluator
 
isNoOutput() - Method in class org.apache.mahout.classifier.df.mapreduce.MapredMapper
 
isNumerical() - Method in enum org.apache.mahout.classifier.df.data.Dataset.Attribute
 
isNumerical(int) - Method in class org.apache.mahout.classifier.df.data.Dataset
Is this a numerical attribute ?
isOrthonormal(double[][], boolean, double) - Static method in class org.apache.mahout.math.hadoop.stochasticsvd.qr.GivensThinSolver
 
isOrthonormalBlocked(Iterable<double[][]>, boolean, double) - Static method in class org.apache.mahout.math.hadoop.stochasticsvd.qr.GivensThinSolver
 
isOutput(Configuration) - Static method in class org.apache.mahout.classifier.df.mapreduce.Builder
Used only for DEBUG purposes.
isOverwrite() - Method in class org.apache.mahout.math.hadoop.stochasticsvd.SSVDSolver
 
isProbabilityScore() - Method in class org.apache.mahout.classifier.evaluation.Auc
 
isSealed() - Method in class org.apache.mahout.classifier.sgd.AbstractOnlineLogisticRegression
 
isSequentialAccess() - Method in class org.apache.mahout.vectorizer.VectorizerConfig
 
isSkipCleanup() - Method in class org.apache.mahout.classifier.bayes.BayesParameters
 
isSubPatternOf(Pattern) - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.Pattern
 
isTraceEnabled() - Method in class org.apache.mahout.vectorizer.encoders.FeatureVectorEncoder
 
isTreeEmpty() - Method in class org.apache.mahout.fpm.pfpgrowth.TransactionTree
 
isTrueFor(Instance) - Method in class org.apache.mahout.classifier.df.data.conditions.Condition
Returns true is the checked instance matches the condition
isTrueFor(Instance) - Method in class org.apache.mahout.classifier.df.data.conditions.Equals
 
isTrueFor(Instance) - Method in class org.apache.mahout.classifier.df.data.conditions.GreaterOrEquals
 
isTrueFor(Instance) - Method in class org.apache.mahout.classifier.df.data.conditions.Lesser
 
isWritesLaxPrecision() - Method in class org.apache.mahout.math.VectorWritable
 
ItemAverageRecommender - Class in org.apache.mahout.cf.taste.impl.recommender
A simple recommender that always estimates preference for an item to be the average of all known preference values for that item.
ItemAverageRecommender(DataModel) - Constructor for class org.apache.mahout.cf.taste.impl.recommender.ItemAverageRecommender
 
ItemBasedRecommender - Interface in org.apache.mahout.cf.taste.recommender
Interface implemented by "item-based" recommenders.
ItemFilterAsVectorAndPrefsReducer - Class in org.apache.mahout.cf.taste.hadoop.item
we use a neat little trick to explicitly filter items for some users: we inject a NaN summand into the preference estimation for those items, which makes AggregateAndRecommendReducer automatically exclude them
ItemFilterAsVectorAndPrefsReducer() - Constructor for class org.apache.mahout.cf.taste.hadoop.item.ItemFilterAsVectorAndPrefsReducer
 
ItemFilterMapper - Class in org.apache.mahout.cf.taste.hadoop.item
map out all user/item pairs to filter, keyed by the itemID
ItemFilterMapper() - Constructor for class org.apache.mahout.cf.taste.hadoop.item.ItemFilterMapper
 
ITEMID_INDEX - Static variable in class org.apache.mahout.cf.taste.hadoop.preparation.PreparePreferenceMatrixJob
 
ItemIDIndexMapper - Class in org.apache.mahout.cf.taste.hadoop.item
 
ItemIDIndexMapper() - Constructor for class org.apache.mahout.cf.taste.hadoop.item.ItemIDIndexMapper
 
ItemIDIndexReducer - Class in org.apache.mahout.cf.taste.hadoop.item
 
ItemIDIndexReducer() - Constructor for class org.apache.mahout.cf.taste.hadoop.item.ItemIDIndexReducer
 
itemIndex(long) - Method in class org.apache.mahout.cf.taste.impl.recommender.svd.AbstractFactorizer
 
itemSimilarities(long, long[]) - Method in class org.apache.mahout.cf.taste.impl.similarity.CachingItemSimilarity
 
itemSimilarities(long, long[]) - Method in class org.apache.mahout.cf.taste.impl.similarity.CityBlockSimilarity
 
itemSimilarities(long, long[]) - Method in class org.apache.mahout.cf.taste.impl.similarity.file.FileItemSimilarity
 
itemSimilarities(long, long[]) - Method in class org.apache.mahout.cf.taste.impl.similarity.GenericItemSimilarity
 
itemSimilarities(long, long[]) - Method in class org.apache.mahout.cf.taste.impl.similarity.LogLikelihoodSimilarity
 
itemSimilarities(long, long[]) - Method in class org.apache.mahout.cf.taste.impl.similarity.TanimotoCoefficientSimilarity
 
itemSimilarities(long, long[]) - Method in interface org.apache.mahout.cf.taste.similarity.ItemSimilarity
A bulk-get version of ItemSimilarity.itemSimilarity(long, long).
itemSimilarity(long, long) - Method in class org.apache.mahout.cf.taste.impl.similarity.CachingItemSimilarity
 
itemSimilarity(long, long) - Method in class org.apache.mahout.cf.taste.impl.similarity.CityBlockSimilarity
 
itemSimilarity(long, long) - Method in class org.apache.mahout.cf.taste.impl.similarity.file.FileItemSimilarity
 
itemSimilarity(long, long) - Method in class org.apache.mahout.cf.taste.impl.similarity.GenericItemSimilarity
Returns the similarity between two items.
itemSimilarity(long, long) - Method in class org.apache.mahout.cf.taste.impl.similarity.LogLikelihoodSimilarity
 
itemSimilarity(long, long) - Method in class org.apache.mahout.cf.taste.impl.similarity.TanimotoCoefficientSimilarity
 
ItemSimilarity - Interface in org.apache.mahout.cf.taste.similarity
Implementations of this interface define a notion of similarity between two items.
itemSimilarity(long, long) - Method in interface org.apache.mahout.cf.taste.similarity.ItemSimilarity
Returns the degree of similarity, of two items, based on the preferences that users have expressed for the items.
ItemSimilarityJob - Class in org.apache.mahout.cf.taste.hadoop.similarity.item
Distributed precomputation of the item-item-similarities for Itembased Collaborative Filtering
ItemSimilarityJob() - Constructor for class org.apache.mahout.cf.taste.hadoop.similarity.item.ItemSimilarityJob
 
ItemSimilarityJob.MostSimilarItemPairsMapper - Class in org.apache.mahout.cf.taste.hadoop.similarity.item
 
ItemSimilarityJob.MostSimilarItemPairsMapper() - Constructor for class org.apache.mahout.cf.taste.hadoop.similarity.item.ItemSimilarityJob.MostSimilarItemPairsMapper
 
ItemUserAverageRecommender - Class in org.apache.mahout.cf.taste.impl.recommender
Like ItemAverageRecommender, except that estimated preferences are adjusted for the users' average preference value.
ItemUserAverageRecommender(DataModel) - Constructor for class org.apache.mahout.cf.taste.impl.recommender.ItemUserAverageRecommender
 
iterate(Iterable<Vector>, ClusterClassifier, int) - Method in class org.apache.mahout.clustering.ClusterIterator
Iterate over data using a prior-trained ClusterClassifier, for a number of iterations
iterate(Iterable<MeanShiftCanopy>, boolean[]) - Method in class org.apache.mahout.clustering.meanshift.MeanShiftCanopyClusterer
 
iterateAll() - Method in class org.apache.mahout.math.hadoop.DistributedRowMatrix
 
iterateMR(Path, Path, Path, int) - Static method in class org.apache.mahout.clustering.ClusterIterator
Iterate over data using a prior-trained ClusterClassifier, for a number of iterations using a mapreduce implementation
iterateSeq(Path, Path, Path, int) - Method in class org.apache.mahout.clustering.ClusterIterator
Iterate over data using a prior-trained ClusterClassifier, for a number of iterations using a sequential implementation
iterateUntilConvergence(double, int, int) - Method in class org.apache.mahout.clustering.lda.cvb.InMemoryCollapsedVariationalBayes0
 
iterateUntilConvergence(double, int, int, double) - Method in class org.apache.mahout.clustering.lda.cvb.InMemoryCollapsedVariationalBayes0
 
ITERATION_BLOCK_SIZE - Static variable in class org.apache.mahout.clustering.lda.cvb.CVB0Driver
 
iterator() - Method in class org.apache.mahout.cf.taste.impl.common.FastIDSet
 
iterator() - Method in class org.apache.mahout.cf.taste.impl.model.BooleanItemPreferenceArray
 
iterator() - Method in class org.apache.mahout.cf.taste.impl.model.BooleanUserPreferenceArray
 
iterator() - Method in class org.apache.mahout.cf.taste.impl.model.GenericItemPreferenceArray
 
iterator() - Method in class org.apache.mahout.cf.taste.impl.model.GenericUserPreferenceArray
 
iterator() - Method in class org.apache.mahout.clustering.lda.cvb.TopicModel
 
iterator() - Method in class org.apache.mahout.common.iterator.FileLineIterable
 
iterator() - Method in class org.apache.mahout.common.iterator.SamplingIterable
 
iterator() - Method in class org.apache.mahout.common.iterator.sequencefile.SequenceFileDirIterable
 
iterator() - Method in class org.apache.mahout.common.iterator.sequencefile.SequenceFileDirValueIterable
 
iterator() - Method in class org.apache.mahout.common.iterator.sequencefile.SequenceFileIterable
 
iterator() - Method in class org.apache.mahout.common.iterator.sequencefile.SequenceFileValueIterable
 
iterator() - Method in class org.apache.mahout.fpm.pfpgrowth.convertors.string.TopKStringPatterns
 
iterator() - Method in class org.apache.mahout.fpm.pfpgrowth.TransactionTree
 
iterator() - Method in class org.apache.mahout.math.hadoop.DistributedRowMatrix
 
IteratorTokenStream - Class in org.apache.mahout.common.lucene
Used to emit tokens from an input string array in the style of TokenStream
IteratorTokenStream(Iterator<String>) - Constructor for class org.apache.mahout.common.lucene.IteratorTokenStream
 

J

JDBCDataModel - Interface in org.apache.mahout.cf.taste.model
 
job() - Method in class org.apache.mahout.math.hadoop.decomposer.DistributedLanczosSolver
 
job() - Method in class org.apache.mahout.math.hadoop.solver.DistributedConjugateGradientSolver
 
JobExecutor - Class in org.apache.mahout.classifier.bayes.mapreduce.common
Base class for executing the Bayes Map/Reduce Jobs

K

K - Static variable in class org.apache.mahout.clustering.kmeans.RandomSeedGenerator
 
KEEP_TEMP_FILES - Static variable in class org.apache.mahout.math.hadoop.DistributedRowMatrix
 
KERNEL_PROFILE_KEY - Static variable in interface org.apache.mahout.clustering.meanshift.MeanShiftCanopyConfigKeys
 
KERNEL_PROFILE_OPTION - Static variable in class org.apache.mahout.common.commandline.DefaultOptionCreator
 
kernelProfileOption() - Static method in class org.apache.mahout.common.commandline.DefaultOptionCreator
 
KEY_GROUPS - Static variable in class org.apache.mahout.common.commandline.MinhashOptionCreator
 
KeyCounterMapper - Class in org.apache.mahout.math.stats.entropy
Emits the key and the count of 1 as VarIntWritable.
KeyCounterMapper() - Constructor for class org.apache.mahout.math.stats.entropy.KeyCounterMapper
 
keyFor(String) - Static method in class org.apache.mahout.common.AbstractJob
Build the option key (--name) from the option name
keyGroupsOption() - Static method in class org.apache.mahout.common.commandline.MinhashOptionCreator
Returns a default command line option for specifying the number of key groups to be used in MinHash clustering
keySet() - Method in class org.apache.mahout.cf.taste.impl.common.FastMap
 
keySetIterator() - Method in class org.apache.mahout.cf.taste.impl.common.FastByIDMap
 
KMeansClusterer - Class in org.apache.mahout.clustering.kmeans
This class implements the k-means clustering algorithm.
KMeansClusterer(DistanceMeasure) - Constructor for class org.apache.mahout.clustering.kmeans.KMeansClusterer
Init the k-means clusterer with the distance measure to use for comparison.
KMeansClusteringPolicy - Class in org.apache.mahout.clustering
This is a simple maximum likelihood clustering policy, suitable for k-means clustering
KMeansClusteringPolicy() - Constructor for class org.apache.mahout.clustering.KMeansClusteringPolicy
 
KMeansClusterMapper - Class in org.apache.mahout.clustering.kmeans
The KMeansClusterMapper is responsible for calculating which points belong to which clusters and outputting the information.
KMeansClusterMapper() - Constructor for class org.apache.mahout.clustering.kmeans.KMeansClusterMapper
 
KMeansCombiner - Class in org.apache.mahout.clustering.kmeans
 
KMeansCombiner() - Constructor for class org.apache.mahout.clustering.kmeans.KMeansCombiner
 
KMeansConfigKeys - Interface in org.apache.mahout.clustering.kmeans
This class holds all config keys that are relevant to be used in the KMeans MapReduce configuration.
KMeansDriver - Class in org.apache.mahout.clustering.kmeans
 
KMeansDriver() - Constructor for class org.apache.mahout.clustering.kmeans.KMeansDriver
 
KMeansMapper - Class in org.apache.mahout.clustering.kmeans
 
KMeansMapper() - Constructor for class org.apache.mahout.clustering.kmeans.KMeansMapper
 
KMeansReducer - Class in org.apache.mahout.clustering.kmeans
 
KMeansReducer() - Constructor for class org.apache.mahout.clustering.kmeans.KMeansReducer
 
KnnItemBasedRecommender - Class in org.apache.mahout.cf.taste.impl.recommender.knn
The weights to compute the final predicted preferences are calculated using linear interpolation, through an Optimizer.
KnnItemBasedRecommender(DataModel, ItemSimilarity, Optimizer, CandidateItemsStrategy, MostSimilarItemsCandidateItemsStrategy, int) - Constructor for class org.apache.mahout.cf.taste.impl.recommender.knn.KnnItemBasedRecommender
 
KnnItemBasedRecommender(DataModel, ItemSimilarity, Optimizer, int) - Constructor for class org.apache.mahout.cf.taste.impl.recommender.knn.KnnItemBasedRecommender
 

L

L1 - Class in org.apache.mahout.classifier.sgd
Implements the Laplacian or bi-exponential prior.
L1() - Constructor for class org.apache.mahout.classifier.sgd.L1
 
L2 - Class in org.apache.mahout.classifier.sgd
Implements the Gaussian prior.
L2(double) - Constructor for class org.apache.mahout.classifier.sgd.L2
 
L2() - Constructor for class org.apache.mahout.classifier.sgd.L2
 
LABEL_COUNT - Static variable in class org.apache.mahout.classifier.bayes.mapreduce.common.BayesConstants
 
LABEL_KEY - Static variable in class org.apache.mahout.classifier.naivebayes.test.TestNaiveBayesDriver
 
LABEL_SUM - Static variable in class org.apache.mahout.classifier.bayes.mapreduce.common.BayesConstants
 
LABEL_THETA_NORMALIZER - Static variable in class org.apache.mahout.classifier.bayes.mapreduce.common.BayesConstants
 
LABEL_THETA_NORMALIZER - Static variable in class org.apache.mahout.classifier.naivebayes.training.TrainNaiveBayesJob
 
labelCode(String) - Method in class org.apache.mahout.classifier.df.data.Dataset
Returns the code used to represent the label value in the data
labels() - Method in class org.apache.mahout.classifier.df.data.Dataset
 
labelWeight(int) - Method in class org.apache.mahout.classifier.naivebayes.NaiveBayesModel
 
labelWeight(int) - Method in class org.apache.mahout.classifier.naivebayes.training.AbstractThetaTrainer
 
lambda(double) - Method in class org.apache.mahout.classifier.sgd.AbstractOnlineLogisticRegression
Chainable configuration option.
lambda(double) - Method in class org.apache.mahout.classifier.sgd.CrossFoldLearner
 
lambda(double) - Method in class org.apache.mahout.classifier.sgd.OnlineLogisticRegression
 
lastTaskId - Variable in class org.apache.mahout.math.hadoop.stochasticsvd.ABtDenseOutJob.QRReducer
 
lastTaskId - Variable in class org.apache.mahout.math.hadoop.stochasticsvd.ABtJob.QRReducer
 
LDADocumentTopicMapper - Class in org.apache.mahout.clustering.lda
 
LDADocumentTopicMapper() - Constructor for class org.apache.mahout.clustering.lda.LDADocumentTopicMapper
 
LDADriver - Class in org.apache.mahout.clustering.lda
Estimates an LDA model from a corpus of documents, which are SparseVectors of word counts.
LDADriver() - Constructor for class org.apache.mahout.clustering.lda.LDADriver
 
LDAInference - Class in org.apache.mahout.clustering.lda
Class for performing infererence on a document, which involves computing (an approximation to) p(word|topic) for each word and topic, and a prior distribution p(topic) for each topic.
LDAInference(LDAState) - Constructor for class org.apache.mahout.clustering.lda.LDAInference
 
LDAInference.InferredDocument - Class in org.apache.mahout.clustering.lda
An estimate of the probabilities for each document.
LDAReducer - Class in org.apache.mahout.clustering.lda
A very simple reducer which simply logSums the input doubles and outputs a new double for sufficient statistics, and sums log likelihoods.
LDAReducer() - Constructor for class org.apache.mahout.clustering.lda.LDAReducer
 
LDASampler - Class in org.apache.mahout.clustering.lda
Takes in a Matrix of topic distributions (such as generated by LDADriver, CVB0Driver or InMemoryCollapsedVariationalBayes0, and constructs a set of samplers over this distribution, which may be sampled from by providing a distribution over topics, and a number of samples desired
LDASampler(Matrix, Random) - Constructor for class org.apache.mahout.clustering.lda.LDASampler
 
LDAState - Class in org.apache.mahout.clustering.lda
 
LDAState(int, int, double, Matrix, double[], double) - Constructor for class org.apache.mahout.clustering.lda.LDAState
 
LDAWordTopicMapper - Class in org.apache.mahout.clustering.lda
Runs inference on the input documents (which are sparse vectors of word counts) and outputs the sufficient statistics for the word-topic assignments.
LDAWordTopicMapper() - Constructor for class org.apache.mahout.clustering.lda.LDAWordTopicMapper
 
Leaf - Class in org.apache.mahout.classifier.df.node
Represents a Leaf node
Leaf(double) - Constructor for class org.apache.mahout.classifier.df.node.Leaf
 
learningRate(double) - Method in class org.apache.mahout.classifier.sgd.CrossFoldLearner
 
learningRate(double) - Method in class org.apache.mahout.classifier.sgd.GradientMachine
Chainable configuration option.
learningRate(double) - Method in class org.apache.mahout.classifier.sgd.OnlineLogisticRegression
Chainable configuration option.
learningRate(double) - Method in class org.apache.mahout.classifier.sgd.PassiveAggressive
Chainable configuration option.
LeastKCache<K extends Comparable<? super K>,V> - Class in org.apache.mahout.fpm.pfpgrowth.fpgrowth
 
LeastKCache(int) - Constructor for class org.apache.mahout.fpm.pfpgrowth.fpgrowth.LeastKCache
 
leastSupport() - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.FrequentPatternMaxHeap
 
length() - Method in class org.apache.mahout.cf.taste.impl.model.BooleanItemPreferenceArray
 
length() - Method in class org.apache.mahout.cf.taste.impl.model.BooleanUserPreferenceArray
 
length() - Method in class org.apache.mahout.cf.taste.impl.model.GenericItemPreferenceArray
 
length() - Method in class org.apache.mahout.cf.taste.impl.model.GenericUserPreferenceArray
 
length() - Method in interface org.apache.mahout.cf.taste.model.PreferenceArray
 
length() - Method in class org.apache.mahout.common.IntegerTuple
Returns the length of the tuple
length() - Method in class org.apache.mahout.common.IntTuple
Returns the length of the tuple
length() - Method in class org.apache.mahout.common.StringTuple
Returns the length of the tuple
length() - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.Pattern
 
lesser(int, double) - Static method in class org.apache.mahout.classifier.df.data.conditions.Condition
Condition that checks if the given attribute has a value "lesser" than the given value
Lesser - Class in org.apache.mahout.classifier.df.data.conditions
True if a given attribute has a value "lesser" than a given value
Lesser(int, double) - Constructor for class org.apache.mahout.classifier.df.data.conditions.Lesser
 
like() - Method in class org.apache.mahout.math.hadoop.stochasticsvd.UpperTriangular
 
like(int, int) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.UpperTriangular
 
LinearModel - Class in org.apache.mahout.classifier.discriminative
Classifies a data point using a hyperplane.
LinearModel(Vector, double, double) - Constructor for class org.apache.mahout.classifier.discriminative.LinearModel
Init a linear model with a hyperplane, distance and displacement.
LinearModel(Vector) - Constructor for class org.apache.mahout.classifier.discriminative.LinearModel
Init a linear model with zero displacement and a threshold of 0.5.
LinearTrainer - Class in org.apache.mahout.classifier.discriminative
Implementors of this class need to provide a way to train linear discriminative classifiers.
LinearTrainer(int, double, double, double) - Constructor for class org.apache.mahout.classifier.discriminative.LinearTrainer
Initialize the trainer.
link(Vector) - Method in class org.apache.mahout.classifier.sgd.AbstractOnlineLogisticRegression
Computes the inverse link function, by default the logistic link function.
link(double) - Method in class org.apache.mahout.classifier.sgd.AbstractOnlineLogisticRegression
Computes the binomial logistic inverse link function.
list() - Static method in enum org.apache.mahout.math.hadoop.similarity.cooccurrence.measures.VectorSimilarityMeasures
 
listOutputFiles(FileSystem, Path) - Static method in class org.apache.mahout.classifier.df.DFUtils
Return a list of all files in the output directory
listOutputFiles(FileSystem, Path) - Static method in class org.apache.mahout.ga.watchmaker.OutputUtils
Lists all files in the output Path
LLRReducer - Class in org.apache.mahout.vectorizer.collocations.llr
Reducer for pass 2 of the collocation discovery job.
LLRReducer() - Constructor for class org.apache.mahout.vectorizer.collocations.llr.LLRReducer
 
LLRReducer.ConcreteLLCallback - Class in org.apache.mahout.vectorizer.collocations.llr
concrete implementation delegates to LogLikelihood class
LLRReducer.ConcreteLLCallback() - Constructor for class org.apache.mahout.vectorizer.collocations.llr.LLRReducer.ConcreteLLCallback
 
LLRReducer.LLCallback - Interface in org.apache.mahout.vectorizer.collocations.llr
provide interface so the input to the llr calculation can be captured for validation in unit testing
LLRReducer.Skipped - Enum in org.apache.mahout.vectorizer.collocations.llr
Counter to track why a particlar entry was skipped
load() - Method in class org.apache.mahout.cf.taste.impl.recommender.svd.FilePersistenceStrategy
 
load() - Method in class org.apache.mahout.cf.taste.impl.recommender.svd.NoPersistenceStrategy
 
load() - Method in interface org.apache.mahout.cf.taste.impl.recommender.svd.PersistenceStrategy
Load a factorization from a persistent store.
load(Configuration, Path) - Static method in class org.apache.mahout.classifier.df.data.Dataset
Loads the dataset from a file
load(Configuration, Path) - Static method in class org.apache.mahout.classifier.df.DecisionForest
Load the forest from a single file or a directory of files
load(Configuration) - Static method in class org.apache.mahout.clustering.spectral.common.VectorCache
Loads the vector from DistributedCache.
load(Configuration, Path) - Static method in class org.apache.mahout.clustering.spectral.common.VectorCache
Loads a Vector from the specified path.
loadAndSumUpperTriangularMatrices(FileSystem, Path, Configuration) - Static method in class org.apache.mahout.math.hadoop.stochasticsvd.SSVDSolver
Load multiplel upper triangular matrices and sum them up.
loadClusters(Configuration, Path) - Static method in class org.apache.mahout.clustering.dirichlet.DirichletClusterMapper
 
loadData(Dataset, FileSystem, Path) - Static method in class org.apache.mahout.classifier.df.data.DataLoader
Loads the data from a file
loadData(Dataset, String[]) - Static method in class org.apache.mahout.classifier.df.data.DataLoader
Loads the data from a String array
loadDataset(Configuration) - Static method in class org.apache.mahout.classifier.df.mapreduce.Builder
Helper method.
loadDistributedRowMatrix(FileSystem, Path, Configuration) - Static method in class org.apache.mahout.math.hadoop.stochasticsvd.SSVDSolver
helper capabiltiy to load distributed row matrices into dense matrix (to support tests mainly).
LoadEvaluator - Class in org.apache.mahout.cf.taste.impl.eval
Simple helper class for running load on a Recommender.
loadFeatureWeight(String, String, double) - Method in class org.apache.mahout.classifier.bayes.InMemoryBayesDatastore
 
loadFeatureWeights(InMemoryBayesDatastore, Path, Configuration) - Static method in class org.apache.mahout.classifier.bayes.SequenceFileModelReader
 
loadLabelWeights(InMemoryBayesDatastore, Path, Configuration) - Static method in class org.apache.mahout.classifier.bayes.SequenceFileModelReader
 
loadModel(InMemoryBayesDatastore, Parameters, Configuration) - Static method in class org.apache.mahout.classifier.bayes.SequenceFileModelReader
 
loadModel(Configuration, Path...) - Static method in class org.apache.mahout.clustering.lda.cvb.TopicModel
 
loadState(Configuration, String, DistributionDescription, double, int) - Static method in class org.apache.mahout.clustering.dirichlet.DirichletMapper
 
LoadStatistics - Class in org.apache.mahout.cf.taste.impl.eval
 
loadSumWeight(InMemoryBayesDatastore, Path, Configuration) - Static method in class org.apache.mahout.classifier.bayes.SequenceFileModelReader
 
loadThetaNormalizer(InMemoryBayesDatastore, Path, Configuration) - Static method in class org.apache.mahout.classifier.bayes.SequenceFileModelReader
 
loadUpperTriangularMatrix(FileSystem, Path, Configuration) - Static method in class org.apache.mahout.math.hadoop.stochasticsvd.SSVDSolver
Load only one upper triangular matrix and issue error if mroe than one is found.
loadWeightMatrix(InMemoryBayesDatastore, Path, Configuration) - Static method in class org.apache.mahout.classifier.bayes.SequenceFileModelReader
 
log - Static variable in interface org.apache.mahout.common.parameters.Parametered
 
LOG_NORMALIZE - Static variable in class org.apache.mahout.vectorizer.common.PartialVectorMerger
 
logLikelihood(int, Vector) - Method in class org.apache.mahout.classifier.AbstractVectorClassifier
Returns a measure of how good the classification for a particular example actually is.
logLikelihood() - Method in class org.apache.mahout.classifier.sgd.CrossFoldLearner
 
logLikelihoodRatio(long, long, long, long) - Method in class org.apache.mahout.vectorizer.collocations.llr.LLRReducer.ConcreteLLCallback
 
logLikelihoodRatio(long, long, long, long) - Method in interface org.apache.mahout.vectorizer.collocations.llr.LLRReducer.LLCallback
 
LogLikelihoodSimilarity - Class in org.apache.mahout.cf.taste.impl.similarity
See http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.14.5962 and http://tdunning.blogspot.com/2008/03/surprise-and-coincidence.html.
LogLikelihoodSimilarity(DataModel) - Constructor for class org.apache.mahout.cf.taste.impl.similarity.LogLikelihoodSimilarity
 
LoglikelihoodSimilarity - Class in org.apache.mahout.math.hadoop.similarity.cooccurrence.measures
 
LoglikelihoodSimilarity() - Constructor for class org.apache.mahout.math.hadoop.similarity.cooccurrence.measures.LoglikelihoodSimilarity
 
logLimit(double, double) - Static method in class org.apache.mahout.ep.Mapping
Maps input to positive values in the open interval (min, max) with 0 going to the geometric mean.
logMemoryStatistics() - Static method in class org.apache.mahout.common.MemoryUtil
Logs current heap memory statistics.
logP(double) - Method in class org.apache.mahout.classifier.sgd.ElasticBandPrior
 
logP(double) - Method in class org.apache.mahout.classifier.sgd.L1
 
logP(double) - Method in class org.apache.mahout.classifier.sgd.L2
 
logP(double) - Method in interface org.apache.mahout.classifier.sgd.PriorFunction
Returns the log of the probability of a particular coefficient value according to the prior.
logP(double) - Method in class org.apache.mahout.classifier.sgd.TPrior
 
logP(double) - Method in class org.apache.mahout.classifier.sgd.UniformPrior
 
logProbWordGivenTopic(int, int) - Method in class org.apache.mahout.clustering.lda.LDAState
 
logsCRCFilter() - Static method in class org.apache.mahout.common.iterator.sequencefile.PathFilters
 
LongPair - Class in org.apache.mahout.common
A simple (ordered) pair of longs.
LongPair(long, long) - Constructor for class org.apache.mahout.common.LongPair
 
LongPrimitiveArrayIterator - Class in org.apache.mahout.cf.taste.impl.common
While long[] is an Iterable, it is not an Iterable<Long>.
LongPrimitiveArrayIterator(long[]) - Constructor for class org.apache.mahout.cf.taste.impl.common.LongPrimitiveArrayIterator
Creates an over an entire array.
LongPrimitiveIterator - Interface in org.apache.mahout.cf.taste.impl.common
Adds notion of iterating over long primitives in the style of an Iterator -- as opposed to iterating over Long.
lookupDataSource(String) - Static method in class org.apache.mahout.cf.taste.impl.common.jdbc.AbstractJDBCComponent
Looks up a DataSource by name from JNDI.
LuceneTextValueEncoder - Class in org.apache.mahout.vectorizer.encoders
Encodes text using a lucene style tokenizer.
LuceneTextValueEncoder(String) - Constructor for class org.apache.mahout.vectorizer.encoders.LuceneTextValueEncoder
 

M

M_KEY - Static variable in interface org.apache.mahout.clustering.fuzzykmeans.FuzzyKMeansConfigKeys
 
M_OPTION - Static variable in class org.apache.mahout.clustering.fuzzykmeans.FuzzyKMeansDriver
 
MahalanobisDistanceMeasure - Class in org.apache.mahout.common.distance
 
MahalanobisDistanceMeasure() - Constructor for class org.apache.mahout.common.distance.MahalanobisDistanceMeasure
 
MAHOUT_GA_EVALUATOR - Static variable in class org.apache.mahout.ga.watchmaker.EvalMapper
Parameter used to store the "stringified" evaluator
MahoutDriver - Class in org.apache.mahout.driver
General-purpose driver class for Mahout programs.
MahoutEvaluator - Class in org.apache.mahout.ga.watchmaker
Generic Mahout distributed evaluator.
MahoutFitnessEvaluator<T> - Class in org.apache.mahout.ga.watchmaker
Watchmaker compatible Fitness Evaluator that delegates the evaluation of the whole population to Mahout.
MahoutFitnessEvaluator(FitnessEvaluator<? super T>) - Constructor for class org.apache.mahout.ga.watchmaker.MahoutFitnessEvaluator
 
main(String[]) - Static method in class org.apache.mahout.cf.taste.hadoop.als.DatasetSplitter
 
main(String[]) - Static method in class org.apache.mahout.cf.taste.hadoop.als.FactorizationEvaluator
 
main(String[]) - Static method in class org.apache.mahout.cf.taste.hadoop.als.ParallelALSFactorizationJob
 
main(String[]) - Static method in class org.apache.mahout.cf.taste.hadoop.als.RecommenderJob
 
main(String[]) - Static method in class org.apache.mahout.cf.taste.hadoop.item.RecommenderJob
 
main(String[]) - Static method in class org.apache.mahout.cf.taste.hadoop.preparation.PreparePreferenceMatrixJob
 
main(String[]) - Static method in class org.apache.mahout.cf.taste.hadoop.pseudo.RecommenderJob
 
main(String[]) - Static method in class org.apache.mahout.cf.taste.hadoop.similarity.item.ItemSimilarityJob
 
main(String[]) - Static method in class org.apache.mahout.cf.taste.hadoop.slopeone.SlopeOneAverageDiffsJob
 
main(String[]) - Static method in class org.apache.mahout.classifier.bayes.TestClassifier
 
main(String[]) - Static method in class org.apache.mahout.classifier.bayes.TrainClassifier
 
main(String[]) - Static method in class org.apache.mahout.classifier.BayesFileFormatter
Run the FileFormatter
main(String[]) - Static method in class org.apache.mahout.classifier.Classify
 
main(String[]) - Static method in class org.apache.mahout.classifier.df.tools.Describe
 
main(String[]) - Static method in class org.apache.mahout.classifier.df.tools.ForestVisualizer
 
main(String[]) - Static method in class org.apache.mahout.classifier.df.tools.Frequencies
 
main(String[]) - Static method in class org.apache.mahout.classifier.df.tools.UDistrib
Launch the uniform distribution tool.
main(String[]) - Static method in class org.apache.mahout.classifier.naivebayes.test.TestNaiveBayesDriver
 
main(String[]) - Static method in class org.apache.mahout.classifier.naivebayes.training.TrainNaiveBayesJob
 
main(String[]) - Static method in class org.apache.mahout.classifier.sequencelearning.hmm.BaumWelchTrainer
 
main(String[]) - Static method in class org.apache.mahout.classifier.sequencelearning.hmm.RandomSequenceGenerator
 
main(String[]) - Static method in class org.apache.mahout.classifier.sequencelearning.hmm.ViterbiEvaluator
 
main(String[]) - Static method in class org.apache.mahout.clustering.canopy.CanopyDriver
 
main(String[]) - Static method in class org.apache.mahout.clustering.dirichlet.DirichletDriver
 
main(String[]) - Static method in class org.apache.mahout.clustering.fuzzykmeans.FuzzyKMeansDriver
 
main(String[]) - Static method in class org.apache.mahout.clustering.kmeans.KMeansDriver
 
main(String[]) - Static method in class org.apache.mahout.clustering.lda.cvb.CVB0Driver
 
main(String[]) - Static method in class org.apache.mahout.clustering.lda.cvb.InMemoryCollapsedVariationalBayes0
 
main(String[]) - Static method in class org.apache.mahout.clustering.lda.LDADriver
 
main(String[]) - Static method in class org.apache.mahout.clustering.meanshift.MeanShiftCanopyDriver
 
main(String[]) - Static method in class org.apache.mahout.clustering.minhash.MinHashDriver
 
main(String[]) - Static method in class org.apache.mahout.clustering.spectral.eigencuts.EigencutsDriver
 
main(String[]) - Static method in class org.apache.mahout.clustering.spectral.kmeans.SpectralKMeansDriver
 
main(String[]) - Static method in class org.apache.mahout.clustering.topdown.postprocessor.ClusterOutputPostProcessorDriver
 
main(String[]) - Static method in class org.apache.mahout.driver.MahoutDriver
 
main(String[]) - Static method in class org.apache.mahout.fpm.pfpgrowth.FPGrowthDriver
 
main(String[]) - Static method in class org.apache.mahout.graph.AdjacencyMatrixJob
 
main(String[]) - Static method in class org.apache.mahout.graph.linkanalysis.PageRankJob
 
main(String[]) - Static method in class org.apache.mahout.graph.linkanalysis.RandomWalkWithRestartJob
 
main(String[]) - Static method in class org.apache.mahout.math.hadoop.decomposer.DistributedLanczosSolver
 
main(String[]) - Static method in class org.apache.mahout.math.hadoop.decomposer.EigenVerificationJob
 
main(String[]) - Static method in class org.apache.mahout.math.hadoop.MatrixMultiplicationJob
 
main(String[]) - Static method in class org.apache.mahout.math.hadoop.similarity.cooccurrence.RowSimilarityJob
 
main(String[]) - Static method in class org.apache.mahout.math.hadoop.similarity.VectorDistanceSimilarityJob
 
main(String[]) - Static method in class org.apache.mahout.math.hadoop.solver.DistributedConjugateGradientSolver
 
main(String[]) - Static method in class org.apache.mahout.math.hadoop.stochasticsvd.SSVDCli
 
main(String[]) - Static method in class org.apache.mahout.math.hadoop.stochasticsvd.SSVDPrototype
 
main(String[]) - Static method in class org.apache.mahout.math.hadoop.TransposeJob
 
main(String[]) - Static method in class org.apache.mahout.math.stats.entropy.ConditionalEntropy
 
main(String[]) - Static method in class org.apache.mahout.math.stats.entropy.Entropy
 
main(String[]) - Static method in class org.apache.mahout.math.stats.entropy.InformationGain
 
main(String[]) - Static method in class org.apache.mahout.math.stats.entropy.InformationGainRatio
 
main(String[]) - Static method in class org.apache.mahout.vectorizer.collocations.llr.CollocDriver
 
main(String[]) - Static method in class org.apache.mahout.vectorizer.EncodedVectorsFromSequenceFiles
 
main(String[]) - Static method in class org.apache.mahout.vectorizer.SparseVectorsFromSequenceFiles
 
main(String[]) - Static method in class org.apache.mahout.Version
 
main2(String[], Configuration) - Static method in class org.apache.mahout.clustering.lda.cvb.InMemoryCollapsedVariationalBayes0
 
majorityLabel(Random) - Method in class org.apache.mahout.classifier.df.data.Data
finds the majority label, breaking ties randomly
This method can be used when the criterion variable is the categorical attribute.
ManhattanDistanceMeasure - Class in org.apache.mahout.common.distance
This class implements a "manhattan distance" metric by summing the absolute values of the difference between each coordinate
ManhattanDistanceMeasure() - Constructor for class org.apache.mahout.common.distance.ManhattanDistanceMeasure
 
map(LongWritable, Text, Mapper<LongWritable, Text, DoubleWritable, NullWritable>.Context) - Method in class org.apache.mahout.cf.taste.hadoop.als.FactorizationEvaluator.PredictRatingsMapper
 
map(LongWritable, Text, Mapper<LongWritable, Text, VarLongWritable, VarLongWritable>.Context) - Method in class org.apache.mahout.cf.taste.hadoop.item.ItemFilterMapper
 
map(LongWritable, Text, Mapper<LongWritable, Text, VarIntWritable, VarLongWritable>.Context) - Method in class org.apache.mahout.cf.taste.hadoop.item.ItemIDIndexMapper
 
map(VarIntWritable, VectorAndPrefsWritable, Mapper<VarIntWritable, VectorAndPrefsWritable, VarLongWritable, PrefAndSimilarityColumnWritable>.Context) - Method in class org.apache.mahout.cf.taste.hadoop.item.PartialMultiplyMapper
 
map(IntWritable, VectorWritable, Mapper<IntWritable, VectorWritable, VarIntWritable, VectorOrPrefWritable>.Context) - Method in class org.apache.mahout.cf.taste.hadoop.item.SimilarityMatrixRowWrapperMapper
 
map(VarLongWritable, VectorWritable, Mapper<VarLongWritable, VectorWritable, VarIntWritable, VectorOrPrefWritable>.Context) - Method in class org.apache.mahout.cf.taste.hadoop.item.UserVectorSplitterMapper
 
map(VarLongWritable, VectorWritable, Mapper<VarLongWritable, VectorWritable, IntWritable, VectorWritable>.Context) - Method in class org.apache.mahout.cf.taste.hadoop.preparation.ToItemVectorsMapper
 
map(LongWritable, Text, Mapper<LongWritable, Text, VarLongWritable, NullWritable>.Context) - Method in class org.apache.mahout.cf.taste.hadoop.pseudo.UserIDsMapper
 
map(IntWritable, VectorWritable, Mapper<IntWritable, VectorWritable, EntityEntityWritable, DoubleWritable>.Context) - Method in class org.apache.mahout.cf.taste.hadoop.similarity.item.ItemSimilarityJob.MostSimilarItemPairsMapper
 
map(LongWritable, Text, Mapper<LongWritable, Text, VarLongWritable, VarLongWritable>.Context) - Method in class org.apache.mahout.cf.taste.hadoop.ToEntityPrefsMapper
 
map(Text, Text, OutputCollector<StringTuple, DoubleWritable>, Reporter) - Method in class org.apache.mahout.classifier.bayes.mapreduce.bayes.BayesClassifierMapper
Parallel Classification
map(StringTuple, DoubleWritable, OutputCollector<StringTuple, DoubleWritable>, Reporter) - Method in class org.apache.mahout.classifier.bayes.mapreduce.bayes.BayesThetaNormalizerMapper
We need to calculate the thetaNormalization factor of each label
map(StringTuple, DoubleWritable, OutputCollector<StringTuple, DoubleWritable>, Reporter) - Method in class org.apache.mahout.classifier.bayes.mapreduce.cbayes.CBayesThetaNormalizerMapper
We need to calculate the idf of each feature in each label
map(Text, Text, OutputCollector<StringTuple, DoubleWritable>, Reporter) - Method in class org.apache.mahout.classifier.bayes.mapreduce.common.BayesFeatureMapper
We need to count the number of times we've seen a term with a given label and we need to output that.
map(StringTuple, DoubleWritable, OutputCollector<StringTuple, DoubleWritable>, Reporter) - Method in class org.apache.mahout.classifier.bayes.mapreduce.common.BayesTfIdfMapper
We need to calculate the Tf-Idf of each feature in each label
map(StringTuple, DoubleWritable, OutputCollector<StringTuple, DoubleWritable>, Reporter) - Method in class org.apache.mahout.classifier.bayes.mapreduce.common.BayesWeightSummerMapper
We need to calculate the weight sums across each label and each feature
map(LongWritable, Text, Mapper<LongWritable, Text, DoubleWritable, Text>.Context) - Method in class org.apache.mahout.classifier.df.mapreduce.Classifier.CMapper
 
map(IntWritable, NullWritable, Mapper<IntWritable, NullWritable, IntWritable, MapredOutput>.Context) - Method in class org.apache.mahout.classifier.df.mapreduce.inmem.InMemMapper
 
map(LongWritable, Text, Mapper<LongWritable, Text, TreeID, MapredOutput>.Context) - Method in class org.apache.mahout.classifier.df.mapreduce.partial.Step1Mapper
 
map(Text, VectorWritable, Mapper<Text, VectorWritable, Text, VectorWritable>.Context) - Method in class org.apache.mahout.classifier.naivebayes.test.BayesTestMapper
 
map(Text, VectorWritable, Mapper<Text, VectorWritable, IntWritable, VectorWritable>.Context) - Method in class org.apache.mahout.classifier.naivebayes.training.IndexInstancesMapper
 
map(IntWritable, VectorWritable, Mapper<IntWritable, VectorWritable, Text, VectorWritable>.Context) - Method in class org.apache.mahout.classifier.naivebayes.training.ThetaMapper
 
map(IntWritable, VectorWritable, Mapper<IntWritable, VectorWritable, Text, VectorWritable>.Context) - Method in class org.apache.mahout.classifier.naivebayes.training.WeightsMapper
 
map(WritableComparable<?>, VectorWritable, Mapper<WritableComparable<?>, VectorWritable, IntWritable, WeightedVectorWritable>.Context) - Method in class org.apache.mahout.clustering.canopy.ClusterMapper
 
map(WritableComparable<?>, VectorWritable, Mapper<WritableComparable<?>, VectorWritable, IntWritable, Cluster>.Context) - Method in class org.apache.mahout.clustering.CIMapper
 
map(WritableComparable<?>, VectorWritable, Mapper<WritableComparable<?>, VectorWritable, IntWritable, WeightedVectorWritable>.Context) - Method in class org.apache.mahout.clustering.dirichlet.DirichletClusterMapper
 
map(WritableComparable<?>, VectorWritable, Mapper<WritableComparable<?>, VectorWritable, Text, VectorWritable>.Context) - Method in class org.apache.mahout.clustering.dirichlet.DirichletMapper
 
map(WritableComparable<?>, VectorWritable, Mapper<WritableComparable<?>, VectorWritable, IntWritable, WeightedVectorWritable>.Context) - Method in class org.apache.mahout.clustering.fuzzykmeans.FuzzyKMeansClusterMapper
 
map(WritableComparable<?>, VectorWritable, Mapper<WritableComparable<?>, VectorWritable, Text, ClusterObservations>.Context) - Method in class org.apache.mahout.clustering.fuzzykmeans.FuzzyKMeansMapper
 
map(WritableComparable<?>, VectorWritable, Mapper<WritableComparable<?>, VectorWritable, IntWritable, WeightedPropertyVectorWritable>.Context) - Method in class org.apache.mahout.clustering.kmeans.KMeansClusterMapper
 
map(WritableComparable<?>, VectorWritable, Mapper<WritableComparable<?>, VectorWritable, Text, ClusterObservations>.Context) - Method in class org.apache.mahout.clustering.kmeans.KMeansMapper
 
map(IntWritable, VectorWritable, Mapper<IntWritable, VectorWritable, IntWritable, VectorWritable>.Context) - Method in class org.apache.mahout.clustering.lda.cvb.CachingCVB0Mapper
 
map(IntWritable, VectorWritable, Mapper<IntWritable, VectorWritable, DoubleWritable, DoubleWritable>.Context) - Method in class org.apache.mahout.clustering.lda.cvb.CachingCVB0PerplexityMapper
 
map(IntWritable, VectorWritable, Mapper<IntWritable, VectorWritable, IntWritable, VectorWritable>.Context) - Method in class org.apache.mahout.clustering.lda.cvb.CVB0DocInferenceMapper
 
map(IntWritable, VectorWritable, Mapper<IntWritable, VectorWritable, IntWritable, VectorWritable>.Context) - Method in class org.apache.mahout.clustering.lda.cvb.CVB0TopicTermVectorNormalizerMapper
 
map(WritableComparable<?>, VectorWritable, Mapper<WritableComparable<?>, VectorWritable, WritableComparable<?>, VectorWritable>.Context) - Method in class org.apache.mahout.clustering.lda.LDADocumentTopicMapper
 
map(WritableComparable<?>, VectorWritable, Mapper<WritableComparable<?>, VectorWritable, IntPairWritable, DoubleWritable>.Context) - Method in class org.apache.mahout.clustering.lda.LDAWordTopicMapper
 
map(WritableComparable<?>, MeanShiftCanopy, Mapper<WritableComparable<?>, MeanShiftCanopy, IntWritable, WeightedVectorWritable>.Context) - Method in class org.apache.mahout.clustering.meanshift.MeanShiftCanopyClusterMapper
 
map(WritableComparable<?>, VectorWritable, Mapper<WritableComparable<?>, VectorWritable, Text, MeanShiftCanopy>.Context) - Method in class org.apache.mahout.clustering.meanshift.MeanShiftCanopyCreatorMapper
 
map(WritableComparable<?>, MeanShiftCanopy, Mapper<WritableComparable<?>, MeanShiftCanopy, Text, MeanShiftCanopy>.Context) - Method in class org.apache.mahout.clustering.meanshift.MeanShiftCanopyMapper
 
map(Text, VectorWritable, Mapper<Text, VectorWritable, Text, Writable>.Context) - Method in class org.apache.mahout.clustering.minhash.MinHashMapper
Hash all items with each function and retain min.
map(LongWritable, Text, Mapper<LongWritable, Text, IntWritable, DistributedRowMatrix.MatrixEntryWritable>.Context) - Method in class org.apache.mahout.clustering.spectral.common.AffinityMatrixInputMapper
 
map(IntWritable, VectorWritable, Mapper<IntWritable, VectorWritable, NullWritable, IntDoublePairWritable>.Context) - Method in class org.apache.mahout.clustering.spectral.common.MatrixDiagonalizeJob.MatrixDiagonalizeMapper
 
map(IntWritable, VectorWritable, Mapper<IntWritable, VectorWritable, IntWritable, VectorWritable>.Context) - Method in class org.apache.mahout.clustering.spectral.common.UnitVectorizerJob.UnitVectorizerMapper
 
map(IntWritable, VectorWritable, Mapper<IntWritable, VectorWritable, IntWritable, VectorWritable>.Context) - Method in class org.apache.mahout.clustering.spectral.common.VectorMatrixMultiplicationJob.VectorMatrixMultiplicationMapper
 
map(IntWritable, VectorWritable, Mapper<IntWritable, VectorWritable, Text, VertexWritable>.Context) - Method in class org.apache.mahout.clustering.spectral.eigencuts.EigencutsAffinityCutsJob.EigencutsAffinityCutsMapper
 
map(IntWritable, VectorWritable, Mapper<IntWritable, VectorWritable, IntWritable, EigencutsSensitivityNode>.Context) - Method in class org.apache.mahout.clustering.spectral.eigencuts.EigencutsSensitivityMapper
 
map(IntWritable, WeightedVectorWritable, Mapper<IntWritable, WeightedVectorWritable, Text, VectorWritable>.Context) - Method in class org.apache.mahout.clustering.topdown.postprocessor.ClusterOutputPostProcessorMapper
The key is the cluster id and the value is the vector.
map(IntWritable, VectorWritable, Mapper<IntWritable, VectorWritable, IntWritable, VectorWritable>.Context) - Method in class org.apache.mahout.common.mapreduce.TransposeMapper
 
map(Text, TopKStringPatterns, Mapper<Text, TopKStringPatterns, Text, TopKStringPatterns>.Context) - Method in class org.apache.mahout.fpm.pfpgrowth.AggregatorMapper
 
map(LongWritable, Text, Mapper<LongWritable, Text, Text, LongWritable>.Context) - Method in class org.apache.mahout.fpm.pfpgrowth.ParallelCountingMapper
 
map(LongWritable, Text, Mapper<LongWritable, Text, IntWritable, TransactionTree>.Context) - Method in class org.apache.mahout.fpm.pfpgrowth.ParallelFPGrowthMapper
 
map(LongWritable, Text, Mapper<LongWritable, Text, LongWritable, DoubleWritable>.Context) - Method in class org.apache.mahout.ga.watchmaker.EvalMapper
 
map(IntWritable, TupleWritable, OutputCollector<IntWritable, VectorWritable>, Reporter) - Method in class org.apache.mahout.math.hadoop.MatrixMultiplicationJob.MatrixMultiplyMapper
 
map(IntWritable, VectorWritable, Mapper<IntWritable, VectorWritable, IntWritable, VectorWritable>.Context) - Method in class org.apache.mahout.math.hadoop.similarity.cooccurrence.RowSimilarityJob.CooccurrencesMapper
 
map(IntWritable, VectorWritable, Mapper<IntWritable, VectorWritable, IntWritable, VectorWritable>.Context) - Method in class org.apache.mahout.math.hadoop.similarity.cooccurrence.RowSimilarityJob.UnsymmetrifyMapper
 
map(IntWritable, VectorWritable, Mapper<IntWritable, VectorWritable, IntWritable, VectorWritable>.Context) - Method in class org.apache.mahout.math.hadoop.similarity.cooccurrence.RowSimilarityJob.VectorNormMapper
 
map(WritableComparable<?>, VectorWritable, Mapper<WritableComparable<?>, VectorWritable, Text, VectorWritable>.Context) - Method in class org.apache.mahout.math.hadoop.similarity.VectorDistanceInvertedMapper
 
map(WritableComparable<?>, VectorWritable, Mapper<WritableComparable<?>, VectorWritable, StringTuple, DoubleWritable>.Context) - Method in class org.apache.mahout.math.hadoop.similarity.VectorDistanceMapper
 
map(IntWritable, Writable, Mapper<IntWritable, Writable, IntWritable, DoubleWritable>.Context) - Method in class org.apache.mahout.math.hadoop.stats.StandardDeviationCalculatorMapper
 
map(Writable, VectorWritable, Mapper<Writable, VectorWritable, SplitPartitionedWritable, DenseBlockWritable>.Context) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.ABtDenseOutJob.ABtMapper
 
map(Writable, VectorWritable, Mapper<Writable, VectorWritable, SplitPartitionedWritable, SparseRowBlockWritable>.Context) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.ABtJob.ABtMapper
 
map(Writable, VectorWritable, Mapper<Writable, VectorWritable, LongWritable, SparseRowBlockWritable>.Context) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.BtJob.BtMapper
We maintain A and QtHat inputs partitioned the same way, so we essentially are performing map-side merge here of A and QtHats except QtHat is stored not row-wise but block-wise.
map(Writable, VectorWritable, Mapper<Writable, VectorWritable, SplitPartitionedWritable, VectorWritable>.Context) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.QJob.QMapper
 
map(Vector) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.qr.QRFirstStep
 
map(Writable, VectorWritable, Mapper<Writable, VectorWritable, Writable, VectorWritable>.Context) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.UJob.UMapper
 
map(IntWritable, VectorWritable, Mapper<IntWritable, VectorWritable, IntWritable, VectorWritable>.Context) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.VJob.VMapper
 
map(Writable, VectorWritable, Mapper<Writable, VectorWritable, IntWritable, VectorWritable>.Context) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.YtYJob.YtYMapper
 
map(IntWritable, VectorWritable, OutputCollector<NullWritable, VectorWritable>, Reporter) - Method in class org.apache.mahout.math.hadoop.TimesSquaredJob.TimesMapper
 
map(T, VectorWritable, OutputCollector<NullWritable, VectorWritable>, Reporter) - Method in class org.apache.mahout.math.hadoop.TimesSquaredJob.TimesSquaredMapper
 
map(IntWritable, VectorWritable, OutputCollector<IntWritable, VectorWritable>, Reporter) - Method in class org.apache.mahout.math.hadoop.TransposeJob.TransposeMapper
 
map(Text, VarIntWritable, Mapper<Text, VarIntWritable, NullWritable, DoubleWritable>.Context) - Method in class org.apache.mahout.math.stats.entropy.CalculateEntropyMapper
 
map(Text, DoubleWritable, Mapper<Text, DoubleWritable, NullWritable, DoubleWritable>.Context) - Method in class org.apache.mahout.math.stats.entropy.CalculateSpecificConditionalEntropyMapper
 
map(Text, Text, Mapper<Text, Text, StringTuple, VarIntWritable>.Context) - Method in class org.apache.mahout.math.stats.entropy.GroupAndCountByKeyAndValueMapper
 
map(Writable, Object, Mapper<Writable, Object, Writable, VarIntWritable>.Context) - Method in class org.apache.mahout.math.stats.entropy.KeyCounterMapper
 
map(StringTuple, VarIntWritable, Mapper<StringTuple, VarIntWritable, Text, VarIntWritable>.Context) - Method in class org.apache.mahout.math.stats.entropy.SpecificConditionalEntropyMapper
 
map(Object, Writable, Mapper<Object, Writable, Writable, VarIntWritable>.Context) - Method in class org.apache.mahout.math.stats.entropy.ValueCounterMapper
 
map(Text, StringTuple, Mapper<Text, StringTuple, GramKey, Gram>.Context) - Method in class org.apache.mahout.vectorizer.collocations.llr.CollocMapper
Collocation finder: pass 1 map phase.
map(Text, Text, Mapper<Text, Text, Text, StringTuple>.Context) - Method in class org.apache.mahout.vectorizer.document.SequenceFileTokenizerMapper
 
map(Text, Text, Mapper<Text, Text, Text, VectorWritable>.Context) - Method in class org.apache.mahout.vectorizer.EncodingMapper
 
map(Text, StringTuple, Mapper<Text, StringTuple, Text, LongWritable>.Context) - Method in class org.apache.mahout.vectorizer.term.TermCountMapper
 
map(WritableComparable<?>, VectorWritable, Mapper<WritableComparable<?>, VectorWritable, IntWritable, LongWritable>.Context) - Method in class org.apache.mahout.vectorizer.term.TermDocumentCountMapper
 
Mapping - Class in org.apache.mahout.ep
Provides coordinate tranformations so that evolution can proceed on the entire space of reals but have the output limited and squished in convenient (and safe) ways.
Mapping.Exponential - Class in org.apache.mahout.ep
 
Mapping.Exponential() - Constructor for class org.apache.mahout.ep.Mapping.Exponential
 
Mapping.Identity - Class in org.apache.mahout.ep
 
Mapping.Identity() - Constructor for class org.apache.mahout.ep.Mapping.Identity
 
Mapping.LogLimit - Class in org.apache.mahout.ep
 
Mapping.LogLimit() - Constructor for class org.apache.mahout.ep.Mapping.LogLimit
 
Mapping.SoftLimit - Class in org.apache.mahout.ep
 
Mapping.SoftLimit() - Constructor for class org.apache.mahout.ep.Mapping.SoftLimit
 
MAPRED_REDUCE_TASKS - Static variable in class org.apache.mahout.clustering.meanshift.MeanShiftCanopyDriver
 
MapredMapper<KEYIN,VALUEIN,KEYOUT,VALUEOUT> - Class in org.apache.mahout.classifier.df.mapreduce
Base class for Mapred mappers.
MapredMapper() - Constructor for class org.apache.mahout.classifier.df.mapreduce.MapredMapper
 
MapredOutput - Class in org.apache.mahout.classifier.df.mapreduce
Used by various implementation to return the results of a build.
Contains a grown tree and and its oob predictions.
MapredOutput() - Constructor for class org.apache.mahout.classifier.df.mapreduce.MapredOutput
 
MapredOutput(Node, int[]) - Constructor for class org.apache.mahout.classifier.df.mapreduce.MapredOutput
 
MapredOutput(Node) - Constructor for class org.apache.mahout.classifier.df.mapreduce.MapredOutput
 
MAPREDUCE_METHOD - Static variable in class org.apache.mahout.common.commandline.DefaultOptionCreator
 
matches(T) - Method in interface org.apache.mahout.cf.taste.impl.common.Cache.MatchPredicate
 
materialize(Path, Configuration) - Static method in class org.apache.mahout.classifier.naivebayes.NaiveBayesModel
 
MatrixDiagonalizeJob - Class in org.apache.mahout.clustering.spectral.common
Given a matrix, this job returns a vector whose i_th element is the sum of all the elements in the i_th row of the original matrix.
MatrixDiagonalizeJob.MatrixDiagonalizeMapper - Class in org.apache.mahout.clustering.spectral.common
 
MatrixDiagonalizeJob.MatrixDiagonalizeMapper() - Constructor for class org.apache.mahout.clustering.spectral.common.MatrixDiagonalizeJob.MatrixDiagonalizeMapper
 
MatrixDiagonalizeJob.MatrixDiagonalizeReducer - Class in org.apache.mahout.clustering.spectral.common
 
MatrixDiagonalizeJob.MatrixDiagonalizeReducer() - Constructor for class org.apache.mahout.clustering.spectral.common.MatrixDiagonalizeJob.MatrixDiagonalizeReducer
 
MatrixMultiplicationJob - Class in org.apache.mahout.math.hadoop
 
MatrixMultiplicationJob() - Constructor for class org.apache.mahout.math.hadoop.MatrixMultiplicationJob
 
MatrixMultiplicationJob.MatrixMultiplicationReducer - Class in org.apache.mahout.math.hadoop
 
MatrixMultiplicationJob.MatrixMultiplicationReducer() - Constructor for class org.apache.mahout.math.hadoop.MatrixMultiplicationJob.MatrixMultiplicationReducer
 
MatrixMultiplicationJob.MatrixMultiplyMapper - Class in org.apache.mahout.math.hadoop
 
MatrixMultiplicationJob.MatrixMultiplyMapper() - Constructor for class org.apache.mahout.math.hadoop.MatrixMultiplicationJob.MatrixMultiplyMapper
 
MatrixUtils - Class in org.apache.mahout.math
 
MatrixWritable - Class in org.apache.mahout.math
 
MatrixWritable() - Constructor for class org.apache.mahout.math.MatrixWritable
 
MatrixWritable(Matrix) - Constructor for class org.apache.mahout.math.MatrixWritable
 
MAX_DF - Static variable in class org.apache.mahout.vectorizer.HighDFWordsPruner
 
MAX_DF - Static variable in class org.apache.mahout.vectorizer.tfidf.TFIDFConverter
 
MAX_HEAPSIZE - Static variable in class org.apache.mahout.fpm.pfpgrowth.PFPGrowth
 
MAX_ITERATIONS_OPTION - Static variable in class org.apache.mahout.common.commandline.DefaultOptionCreator
 
MAX_ITERATIONS_PER_DOC - Static variable in class org.apache.mahout.clustering.lda.cvb.CVB0Driver
 
MAX_NGRAMS - Static variable in class org.apache.mahout.vectorizer.DictionaryVectorizer
 
MAX_PER_GROUP - Static variable in class org.apache.mahout.fpm.pfpgrowth.PFPGrowth
 
MAX_REDUCERS_OPTION - Static variable in class org.apache.mahout.common.commandline.DefaultOptionCreator
 
MAX_SHINGLE_SIZE - Static variable in class org.apache.mahout.vectorizer.collocations.llr.CollocMapper
 
MAX_TREEID - Static variable in class org.apache.mahout.classifier.df.mapreduce.partial.TreeID
 
maxDepth() - Method in class org.apache.mahout.classifier.df.node.CategoricalNode
 
maxDepth() - Method in class org.apache.mahout.classifier.df.node.Leaf
 
maxDepth() - Method in class org.apache.mahout.classifier.df.node.Node
 
maxDepth() - Method in class org.apache.mahout.classifier.df.node.NumericalNode
 
maxindex(Random, int[]) - Static method in class org.apache.mahout.classifier.df.data.DataUtils
return the index of the maximum of the array, breaking ties randomly
maxIterationsOption() - Static method in class org.apache.mahout.common.commandline.DefaultOptionCreator
Returns a default command line option for specification of max number of iterations.
maxTargetValue(int) - Method in class org.apache.mahout.classifier.sgd.CsvRecordFactory
Defines the number of target variable categories, but allows this parser to pick encodings for them as they appear.
maxTargetValue(int) - Method in interface org.apache.mahout.classifier.sgd.RecordFactory
 
maybePersist(Factorization) - Method in class org.apache.mahout.cf.taste.impl.recommender.svd.FilePersistenceStrategy
 
maybePersist(Factorization) - Method in class org.apache.mahout.cf.taste.impl.recommender.svd.NoPersistenceStrategy
 
maybePersist(Factorization) - Method in interface org.apache.mahout.cf.taste.impl.recommender.svd.PersistenceStrategy
Write a factorization to a persistent store unless it already contains an identical factorization.
maybePut(Map<String, String>, CommandLine, Option...) - Static method in class org.apache.mahout.common.AbstractJob
 
maybeRefresh(Collection<Refreshable>, Refreshable) - Static method in class org.apache.mahout.cf.taste.impl.common.RefreshHelper
Adds the specified Refreshable to the given collection of Refreshables if it is not already there and immediately refreshes it.
maybeSample(Vector, int) - Static method in class org.apache.mahout.math.hadoop.similarity.cooccurrence.Vectors
 
maybeWrapIterable(Iterable<T>, double) - Static method in class org.apache.mahout.common.iterator.SamplingIterable
 
maybeWrapIterator(LongPrimitiveIterator, double) - Static method in class org.apache.mahout.cf.taste.impl.common.SamplingLongPrimitiveIterator
 
meanMaxDepth() - Method in class org.apache.mahout.classifier.df.DecisionForest
 
meanNbNodes() - Method in class org.apache.mahout.classifier.df.DecisionForest
 
MeanShiftCanopy - Class in org.apache.mahout.clustering.meanshift
This class models a canopy as a center point, the number of points that are contained within it according to the application of some distance metric, and a point total which is the sum of all the points and is used to compute the centroid when needed.
MeanShiftCanopy() - Constructor for class org.apache.mahout.clustering.meanshift.MeanShiftCanopy
Used for Writable
MeanShiftCanopy(Vector, int, DistanceMeasure) - Constructor for class org.apache.mahout.clustering.meanshift.MeanShiftCanopy
Create a new Canopy containing the given point
MeanShiftCanopyClusterer - Class in org.apache.mahout.clustering.meanshift
 
MeanShiftCanopyClusterer(Configuration) - Constructor for class org.apache.mahout.clustering.meanshift.MeanShiftCanopyClusterer
 
MeanShiftCanopyClusterer(DistanceMeasure, IKernelProfile, double, double, double, boolean) - Constructor for class org.apache.mahout.clustering.meanshift.MeanShiftCanopyClusterer
 
MeanShiftCanopyClusterMapper - Class in org.apache.mahout.clustering.meanshift
 
MeanShiftCanopyClusterMapper() - Constructor for class org.apache.mahout.clustering.meanshift.MeanShiftCanopyClusterMapper
 
MeanShiftCanopyConfigKeys - Interface in org.apache.mahout.clustering.meanshift
 
MeanShiftCanopyCreatorMapper - Class in org.apache.mahout.clustering.meanshift
 
MeanShiftCanopyCreatorMapper() - Constructor for class org.apache.mahout.clustering.meanshift.MeanShiftCanopyCreatorMapper
 
MeanShiftCanopyDriver - Class in org.apache.mahout.clustering.meanshift
This class implements the driver for Mean Shift Canopy clustering
MeanShiftCanopyDriver() - Constructor for class org.apache.mahout.clustering.meanshift.MeanShiftCanopyDriver
 
MeanShiftCanopyMapper - Class in org.apache.mahout.clustering.meanshift
 
MeanShiftCanopyMapper() - Constructor for class org.apache.mahout.clustering.meanshift.MeanShiftCanopyMapper
 
MeanShiftCanopyReducer - Class in org.apache.mahout.clustering.meanshift
 
MeanShiftCanopyReducer() - Constructor for class org.apache.mahout.clustering.meanshift.MeanShiftCanopyReducer
 
MemoryDiffStorage - Class in org.apache.mahout.cf.taste.impl.recommender.slopeone
An implementation of DiffStorage that merely stores item-item diffs in memory.
MemoryDiffStorage(DataModel, Weighting, long) - Constructor for class org.apache.mahout.cf.taste.impl.recommender.slopeone.MemoryDiffStorage
See SlopeOneRecommender for the meaning of stdDevWeighted.
MemoryIDMigrator - Class in org.apache.mahout.cf.taste.impl.model
Implementation which stores the reverse long-to-String mapping in memory.
MemoryIDMigrator() - Constructor for class org.apache.mahout.cf.taste.impl.model.MemoryIDMigrator
 
MemoryUtil - Class in org.apache.mahout.common
Memory utilities.
merge(ConfusionMatrix) - Method in class org.apache.mahout.classifier.ConfusionMatrix
 
merge(TopKStringPatterns, int) - Method in class org.apache.mahout.fpm.pfpgrowth.convertors.string.TopKStringPatterns
 
merge(Iterable<VectorWritable>) - Static method in class org.apache.mahout.math.hadoop.similarity.cooccurrence.Vectors
 
merge(Iterator<VectorWritable>) - Static method in class org.apache.mahout.math.VectorWritable
 
mergeCanopy(MeanShiftCanopy, Collection<MeanShiftCanopy>) - Method in class org.apache.mahout.clustering.meanshift.MeanShiftCanopyClusterer
Merge the given canopy into the canopies list.
mergePartialVectors(Iterable<Path>, Path, Configuration, float, boolean, int, boolean, boolean, int) - Static method in class org.apache.mahout.vectorizer.common.PartialVectorMerger
Merge all the partial RandomAccessSparseVectors into the complete Document RandomAccessSparseVector
mergePartialVectors(Iterable<Path>, Path, Configuration, float, boolean, int) - Static method in class org.apache.mahout.vectorizer.HighDFWordsPruner
 
mergeQrDown(double[][], double[][], double[][]) - Static method in class org.apache.mahout.math.hadoop.stochasticsvd.qr.GivensThinSolver
 
mergeQrDown(UpperTriangular, double[][], UpperTriangular) - Static method in class org.apache.mahout.math.hadoop.stochasticsvd.qr.GivensThinSolver
 
mergeQrUp(double[][], double[][], double[][]) - Static method in class org.apache.mahout.math.hadoop.stochasticsvd.qr.GivensThinSolver
 
mergeQrUp(double[][], UpperTriangular, UpperTriangular) - Static method in class org.apache.mahout.math.hadoop.stochasticsvd.qr.GivensThinSolver
 
mergeR(UpperTriangular, UpperTriangular) - Static method in class org.apache.mahout.math.hadoop.stochasticsvd.qr.GivensThinSolver
 
mergeR(double[][], double[][]) - Static method in class org.apache.mahout.math.hadoop.stochasticsvd.qr.GivensThinSolver
 
mergeRonQ(UpperTriangular, UpperTriangular, double[][], double[][]) - Static method in class org.apache.mahout.math.hadoop.stochasticsvd.qr.GivensThinSolver
 
mergeRonQ(double[][], double[][], double[][], double[][]) - Static method in class org.apache.mahout.math.hadoop.stochasticsvd.qr.GivensThinSolver
 
MergeVectorsCombiner - Class in org.apache.mahout.common.mapreduce
 
MergeVectorsCombiner() - Constructor for class org.apache.mahout.common.mapreduce.MergeVectorsCombiner
 
MergeVectorsReducer - Class in org.apache.mahout.common.mapreduce
 
MergeVectorsReducer() - Constructor for class org.apache.mahout.common.mapreduce.MergeVectorsReducer
 
METADATA_FILE - Static variable in class org.apache.mahout.math.hadoop.decomposer.HdfsBackedLanczosState
 
METHOD_OPTION - Static variable in class org.apache.mahout.common.commandline.DefaultOptionCreator
 
methodOption() - Static method in class org.apache.mahout.common.commandline.DefaultOptionCreator
Returns a default command line option for specification of sequential or parallel operation.
MIN_CLUSTER_SIZE - Static variable in class org.apache.mahout.common.commandline.MinhashOptionCreator
 
MIN_DF - Static variable in class org.apache.mahout.vectorizer.tfidf.TFIDFConverter
 
MIN_LLR - Static variable in class org.apache.mahout.vectorizer.collocations.llr.LLRReducer
 
MIN_PREFERENCES_PER_USER - Static variable in class org.apache.mahout.cf.taste.hadoop.item.ToUserVectorsReducer
 
MIN_SUPPORT - Static variable in class org.apache.mahout.fpm.pfpgrowth.PFPGrowth
 
MIN_SUPPORT - Static variable in class org.apache.mahout.vectorizer.collocations.llr.CollocReducer
 
MIN_SUPPORT - Static variable in class org.apache.mahout.vectorizer.DictionaryVectorizer
 
MIN_VECTOR_SIZE - Static variable in class org.apache.mahout.common.commandline.MinhashOptionCreator
 
minClusterSizeOption() - Static method in class org.apache.mahout.common.commandline.MinhashOptionCreator
Returns a default command line option for specifying the minimum cluster size in MinHash clustering
MinHashDriver - Class in org.apache.mahout.clustering.minhash
 
MinHashDriver() - Constructor for class org.apache.mahout.clustering.minhash.MinHashDriver
 
MinHashMapper - Class in org.apache.mahout.clustering.minhash
 
MinHashMapper() - Constructor for class org.apache.mahout.clustering.minhash.MinHashMapper
 
MinhashOptionCreator - Class in org.apache.mahout.common.commandline
 
MinHashReducer - Class in org.apache.mahout.clustering.minhash
 
MinHashReducer() - Constructor for class org.apache.mahout.clustering.minhash.MinHashReducer
 
MinK<T> - Class in org.apache.mahout.cf.taste.common
this class will preserve the k minimum elements of all elements it has been offered
MinK(int, Comparator<? super T>) - Constructor for class org.apache.mahout.cf.taste.common.MinK
 
MinkowskiDistanceMeasure - Class in org.apache.mahout.common.distance
Implement Minkowski distance, a real-valued generalization of the integral L(n) distances: Manhattan = L1, Euclidean = L2.
MinkowskiDistanceMeasure() - Constructor for class org.apache.mahout.common.distance.MinkowskiDistanceMeasure
 
MinkowskiDistanceMeasure(double) - Constructor for class org.apache.mahout.common.distance.MinkowskiDistanceMeasure
 
minVectorSizeOption() - Static method in class org.apache.mahout.common.commandline.MinhashOptionCreator
Returns a default command line option for specifying the min size of the vector to hash Should one out of ("linear","polynomial","murmur")
MixedGradient - Class in org.apache.mahout.classifier.sgd
Provides a stochastic mixture of ranking updates and normal logistic updates.
MixedGradient(double, int) - Constructor for class org.apache.mahout.classifier.sgd.MixedGradient
 
Model<O> - Interface in org.apache.mahout.clustering
A model is a probability distribution over observed data points and allows the probability of any data point to be computed.
MODEL_DISTRIBUTION_CLASS_OPTION - Static variable in class org.apache.mahout.clustering.dirichlet.DirichletDriver
 
MODEL_DISTRIBUTION_KEY - Static variable in class org.apache.mahout.clustering.dirichlet.DirichletDriver
 
MODEL_PROTOTYPE_CLASS_OPTION - Static variable in class org.apache.mahout.clustering.dirichlet.DirichletDriver
 
MODEL_TEMP_DIR - Static variable in class org.apache.mahout.clustering.lda.cvb.CVB0Driver
 
MODEL_WEIGHT - Static variable in class org.apache.mahout.clustering.lda.cvb.CVB0Driver
 
ModelDissector - Class in org.apache.mahout.classifier.sgd
Uses sample data to reverse engineer a feature-hashed model.
ModelDissector() - Constructor for class org.apache.mahout.classifier.sgd.ModelDissector
 
ModelDissector.Weight - Class in org.apache.mahout.classifier.sgd
 
ModelDissector.Weight(String, Vector) - Constructor for class org.apache.mahout.classifier.sgd.ModelDissector.Weight
 
ModelDissector.Weight(String, Vector, int) - Constructor for class org.apache.mahout.classifier.sgd.ModelDissector.Weight
 
ModelDistribution<O> - Interface in org.apache.mahout.clustering
A model distribution allows us to sample a model from its prior distribution.
modelLikelihood(HmmModel, int[], boolean) - Static method in class org.apache.mahout.classifier.sequencelearning.hmm.HmmEvaluator
Returns the likelihood that a given output sequence was produced by the given model.
modelLikelihood(Matrix, boolean) - Static method in class org.apache.mahout.classifier.sequencelearning.hmm.HmmEvaluator
Computes the likelihood that a given output sequence was computed by a given model using the alpha values computed by the forward algorithm.
modelLikelihood(HmmModel, int[], Matrix, boolean) - Static method in class org.apache.mahout.classifier.sequencelearning.hmm.HmmEvaluator
Computes the likelihood that a given output sequence was computed by a given model.
modelPath(Path, int) - Static method in class org.apache.mahout.clustering.lda.cvb.CVB0Driver
 
ModelSerializer - Class in org.apache.mahout.classifier.sgd
Provides the ability to store SGD model-related objects as binary files.
ModelTrainer - Class in org.apache.mahout.clustering.lda.cvb
Multithreaded LDA model trainer class, which primarily operates by running a "map/reduce" operation, all in memory locally (ie not a hadoop job!) : the "map" operation is to take the "read-only" TopicModel and use it to iteratively learn the p(topic|term, doc) distribution for documents (this can be done in parallel across many documents, as the "read-only" model is, well, read-only.
ModelTrainer(TopicModel, TopicModel, int, int, int) - Constructor for class org.apache.mahout.clustering.lda.cvb.ModelTrainer
 
ModelTrainer(TopicModel, int, int, int) - Constructor for class org.apache.mahout.clustering.lda.cvb.ModelTrainer
WARNING: this constructor may not lead to good behavior.
mostSimilarItems(long, int) - Method in class org.apache.mahout.cf.taste.impl.recommender.GenericItemBasedRecommender
 
mostSimilarItems(long, int, Rescorer<LongPair>) - Method in class org.apache.mahout.cf.taste.impl.recommender.GenericItemBasedRecommender
 
mostSimilarItems(long[], int) - Method in class org.apache.mahout.cf.taste.impl.recommender.GenericItemBasedRecommender
 
mostSimilarItems(long[], int, Rescorer<LongPair>) - Method in class org.apache.mahout.cf.taste.impl.recommender.GenericItemBasedRecommender
 
mostSimilarItems(long[], int, boolean) - Method in class org.apache.mahout.cf.taste.impl.recommender.GenericItemBasedRecommender
 
mostSimilarItems(long[], int, Rescorer<LongPair>, boolean) - Method in class org.apache.mahout.cf.taste.impl.recommender.GenericItemBasedRecommender
 
mostSimilarItems(long, int) - Method in interface org.apache.mahout.cf.taste.recommender.ItemBasedRecommender
 
mostSimilarItems(long, int, Rescorer<LongPair>) - Method in interface org.apache.mahout.cf.taste.recommender.ItemBasedRecommender
 
mostSimilarItems(long[], int) - Method in interface org.apache.mahout.cf.taste.recommender.ItemBasedRecommender
 
mostSimilarItems(long[], int, Rescorer<LongPair>) - Method in interface org.apache.mahout.cf.taste.recommender.ItemBasedRecommender
 
mostSimilarItems(long[], int, boolean) - Method in interface org.apache.mahout.cf.taste.recommender.ItemBasedRecommender
 
mostSimilarItems(long[], int, Rescorer<LongPair>, boolean) - Method in interface org.apache.mahout.cf.taste.recommender.ItemBasedRecommender
 
MostSimilarItemsCandidateItemsStrategy - Interface in org.apache.mahout.cf.taste.recommender
Used to retrieve all items that could possibly be similar
mostSimilarUserIDs(long, int) - Method in class org.apache.mahout.cf.taste.impl.recommender.GenericUserBasedRecommender
 
mostSimilarUserIDs(long, int, Rescorer<LongPair>) - Method in class org.apache.mahout.cf.taste.impl.recommender.GenericUserBasedRecommender
 
mostSimilarUserIDs(long, int) - Method in interface org.apache.mahout.cf.taste.recommender.UserBasedRecommender
 
mostSimilarUserIDs(long, int, Rescorer<LongPair>) - Method in interface org.apache.mahout.cf.taste.recommender.UserBasedRecommender
 
MultiLabelVectorWritable - Class in org.apache.mahout.math
Writable to handle serialization of a vector and a variable list of associated label indexes.
MultiLabelVectorWritable() - Constructor for class org.apache.mahout.math.MultiLabelVectorWritable
 
MultiLabelVectorWritable(Vector, int[]) - Constructor for class org.apache.mahout.math.MultiLabelVectorWritable
 
MultiTransactionTreeIterator - Class in org.apache.mahout.fpm.pfpgrowth
Iterates over multiple transaction trees to produce a single iterator of transactions
MultiTransactionTreeIterator(Iterator<Pair<IntArrayList, Long>>) - Constructor for class org.apache.mahout.fpm.pfpgrowth.MultiTransactionTreeIterator
 
murmur64(long, int, long) - Static method in class org.apache.mahout.math.hadoop.stochasticsvd.Omega
Shortened version for data < 8 bytes packed into len lowest bytes of val.
murmur64(byte[], int, int, long) - Static method in class org.apache.mahout.math.hadoop.stochasticsvd.Omega
 
mutate() - Method in class org.apache.mahout.ep.State
Clones this state with a random change in position.
mutatePopulation(int) - Method in class org.apache.mahout.ep.EvolutionaryProcess
Nuke all but a few of the current population and then repopulate with variants of the survivors.
MySQLJDBCIDMigrator - Class in org.apache.mahout.cf.taste.impl.model
An implementation for MySQL.
MySQLJDBCIDMigrator(DataSource) - Constructor for class org.apache.mahout.cf.taste.impl.model.MySQLJDBCIDMigrator
 
MySQLJDBCIDMigrator(DataSource, String, String, String) - Constructor for class org.apache.mahout.cf.taste.impl.model.MySQLJDBCIDMigrator
 

N

NaiveBayesModel - Class in org.apache.mahout.classifier.naivebayes
NaiveBayesModel holds the weight Matrix, the feature and label sums and the weight normalizer vectors.
NaiveBayesModel(Matrix, Vector, Vector, Vector, float) - Constructor for class org.apache.mahout.classifier.naivebayes.NaiveBayesModel
 
name() - Method in class org.apache.mahout.common.parameters.AbstractParameter
 
name() - Method in interface org.apache.mahout.common.parameters.Parameter
 
NAMED_VECTOR - Static variable in class org.apache.mahout.vectorizer.common.PartialVectorMerger
 
nbAttributes() - Method in class org.apache.mahout.classifier.df.data.Dataset
 
nbInstances() - Method in class org.apache.mahout.classifier.df.data.Dataset
 
nblabels() - Method in class org.apache.mahout.classifier.df.data.Dataset
 
nbNodes() - Method in class org.apache.mahout.classifier.df.DecisionForest
 
nbNodes() - Method in class org.apache.mahout.classifier.df.node.CategoricalNode
 
nbNodes() - Method in class org.apache.mahout.classifier.df.node.Leaf
 
nbNodes() - Method in class org.apache.mahout.classifier.df.node.Node
 
nbNodes() - Method in class org.apache.mahout.classifier.df.node.NumericalNode
 
nbTrees(int, int, int) - Static method in class org.apache.mahout.classifier.df.mapreduce.partial.Step1Mapper
Compute the number of trees for a given partition.
nbValues(int) - Method in class org.apache.mahout.classifier.df.data.Dataset
 
NearestNeighborClusterSimilarity - Class in org.apache.mahout.cf.taste.impl.recommender
Defines cluster similarity as the largest similarity between any two users in the clusters -- that is, it says that clusters are close when some pair of their members has high similarity.
NearestNeighborClusterSimilarity(UserSimilarity) - Constructor for class org.apache.mahout.cf.taste.impl.recommender.NearestNeighborClusterSimilarity
Constructs a based on the given UserSimilarity.
NearestNeighborClusterSimilarity(UserSimilarity, double) - Constructor for class org.apache.mahout.cf.taste.impl.recommender.NearestNeighborClusterSimilarity
Constructs a based on the given UserSimilarity.
NearestNUserNeighborhood - Class in org.apache.mahout.cf.taste.impl.neighborhood
Computes a neighborhood consisting of the nearest n users to a given user.
NearestNUserNeighborhood(int, UserSimilarity, DataModel) - Constructor for class org.apache.mahout.cf.taste.impl.neighborhood.NearestNUserNeighborhood
 
NearestNUserNeighborhood(int, double, UserSimilarity, DataModel) - Constructor for class org.apache.mahout.cf.taste.impl.neighborhood.NearestNUserNeighborhood
 
NearestNUserNeighborhood(int, double, UserSimilarity, DataModel, double) - Constructor for class org.apache.mahout.cf.taste.impl.neighborhood.NearestNUserNeighborhood
 
newCall() - Method in class org.apache.mahout.common.TimingStatistics
 
next() - Method in class org.apache.mahout.cf.taste.impl.common.AbstractLongPrimitiveIterator
 
next() - Method in class org.apache.mahout.cf.taste.impl.common.LongPrimitiveArrayIterator
 
next(int) - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.FPTree
 
next() - Method in class org.apache.mahout.math.hadoop.stochasticsvd.qr.QRLastStep
 
nextKeyValue() - Method in class org.apache.mahout.classifier.df.mapreduce.inmem.InMemInputFormat.InMemRecordReader
 
nextLong() - Method in class org.apache.mahout.cf.taste.impl.common.LongPrimitiveArrayIterator
 
nextLong() - Method in interface org.apache.mahout.cf.taste.impl.common.LongPrimitiveIterator
 
nextLong() - Method in class org.apache.mahout.cf.taste.impl.common.SamplingLongPrimitiveIterator
 
nextStep() - Method in class org.apache.mahout.classifier.sgd.AbstractOnlineLogisticRegression
 
nextStep(int) - Method in class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression
 
NGRAM_OUTPUT_DIRECTORY - Static variable in class org.apache.mahout.vectorizer.collocations.llr.CollocDriver
 
NGRAM_TOTAL - Static variable in class org.apache.mahout.vectorizer.collocations.llr.LLRReducer
 
NGrams - Class in org.apache.mahout.common.nlp
 
NGrams(String, int) - Constructor for class org.apache.mahout.common.nlp.NGrams
 
NO_LIMIT_FACTOR - Static variable in class org.apache.mahout.cf.taste.impl.recommender.SamplingCandidateItemsStrategy
Specify this value as a factor to mean no limit.
NO_MAX_SIZE - Static variable in class org.apache.mahout.cf.taste.impl.common.FastByIDMap
 
NO_MAX_SIZE - Static variable in class org.apache.mahout.cf.taste.impl.common.FastMap
 
NO_NORM - Static variable in interface org.apache.mahout.math.hadoop.similarity.cooccurrence.measures.VectorSimilarityMeasure
 
NO_NORMALIZING - Static variable in class org.apache.mahout.vectorizer.common.PartialVectorMerger
 
NO_THRESHOLD - Static variable in class org.apache.mahout.math.hadoop.similarity.cooccurrence.RowSimilarityJob
 
Node - Class in org.apache.mahout.classifier.df.node
Represents an abstract node of a decision tree
Node() - Constructor for class org.apache.mahout.classifier.df.node.Node
 
Node.Type - Enum in org.apache.mahout.classifier.df.node
 
NonNegativeQuadraticOptimizer - Class in org.apache.mahout.cf.taste.impl.recommender.knn
Non-negative Quadratic Optimization.
NonNegativeQuadraticOptimizer() - Constructor for class org.apache.mahout.cf.taste.impl.recommender.knn.NonNegativeQuadraticOptimizer
 
NoPersistenceStrategy - Class in org.apache.mahout.cf.taste.impl.recommender.svd
A PersistenceStrategy which does nothing.
NoPersistenceStrategy() - Constructor for class org.apache.mahout.cf.taste.impl.recommender.svd.NoPersistenceStrategy
 
norm(Vector) - Method in class org.apache.mahout.math.hadoop.similarity.cooccurrence.measures.CosineSimilarity
 
norm(Vector) - Method in class org.apache.mahout.math.hadoop.similarity.cooccurrence.measures.CountbasedMeasure
 
norm(Vector) - Method in class org.apache.mahout.math.hadoop.similarity.cooccurrence.measures.EuclideanDistanceSimilarity
 
norm(Vector) - Method in interface org.apache.mahout.math.hadoop.similarity.cooccurrence.measures.VectorSimilarityMeasure
 
NORMALIZATION_POWER - Static variable in class org.apache.mahout.vectorizer.common.PartialVectorMerger
 
normalize(Vector) - Method in class org.apache.mahout.math.hadoop.similarity.cooccurrence.measures.CosineSimilarity
 
normalize(Vector) - Method in class org.apache.mahout.math.hadoop.similarity.cooccurrence.measures.CountbasedMeasure
 
normalize(Vector) - Method in class org.apache.mahout.math.hadoop.similarity.cooccurrence.measures.EuclideanDistanceSimilarity
 
normalize(Vector) - Method in class org.apache.mahout.math.hadoop.similarity.cooccurrence.measures.PearsonCorrelationSimilarity
 
normalize(Vector) - Method in interface org.apache.mahout.math.hadoop.similarity.cooccurrence.measures.VectorSimilarityMeasure
 
normalizeModel(HmmModel) - Static method in class org.apache.mahout.classifier.sequencelearning.hmm.HmmUtils
Function used to normalize the probabilities of a given HMM model
NormalKernelProfile - Class in org.apache.mahout.common.kernel
 
NormalKernelProfile() - Constructor for class org.apache.mahout.common.kernel.NormalKernelProfile
 
NoSuchItemException - Exception in org.apache.mahout.cf.taste.common
 
NoSuchItemException() - Constructor for exception org.apache.mahout.cf.taste.common.NoSuchItemException
 
NoSuchItemException(long) - Constructor for exception org.apache.mahout.cf.taste.common.NoSuchItemException
 
NoSuchItemException(String) - Constructor for exception org.apache.mahout.cf.taste.common.NoSuchItemException
 
NoSuchUserException - Exception in org.apache.mahout.cf.taste.common
 
NoSuchUserException() - Constructor for exception org.apache.mahout.cf.taste.common.NoSuchUserException
 
NoSuchUserException(long) - Constructor for exception org.apache.mahout.cf.taste.common.NoSuchUserException
 
NoSuchUserException(String) - Constructor for exception org.apache.mahout.cf.taste.common.NoSuchUserException
 
NullRescorer<T> - Class in org.apache.mahout.cf.taste.impl.recommender
A simple Rescorer which always returns the original score.
NUM_CLUSTERS_KEY - Static variable in class org.apache.mahout.clustering.dirichlet.DirichletDriver
 
NUM_CLUSTERS_OPTION - Static variable in class org.apache.mahout.common.commandline.DefaultOptionCreator
 
NUM_FLAGS - Static variable in class org.apache.mahout.math.VectorWritable
 
NUM_GROUPS - Static variable in class org.apache.mahout.fpm.pfpgrowth.PFPGrowth
 
NUM_GROUPS_DEFAULT - Static variable in class org.apache.mahout.fpm.pfpgrowth.PFPGrowth
 
NUM_HASH_FUNCTIONS - Static variable in class org.apache.mahout.common.commandline.MinhashOptionCreator
 
NUM_REDUCE_TASKS - Static variable in class org.apache.mahout.clustering.lda.cvb.CVB0Driver
 
NUM_REDUCERS - Static variable in class org.apache.mahout.common.commandline.MinhashOptionCreator
 
NUM_ROWS_KEY - Static variable in class org.apache.mahout.math.hadoop.TransposeJob
 
NUM_TERMS - Static variable in class org.apache.mahout.clustering.lda.cvb.CVB0Driver
 
NUM_TOPICS - Static variable in class org.apache.mahout.clustering.lda.cvb.CVB0Driver
 
NUM_TRAIN_THREADS - Static variable in class org.apache.mahout.clustering.lda.cvb.CVB0Driver
 
NUM_UPDATE_THREADS - Static variable in class org.apache.mahout.clustering.lda.cvb.CVB0Driver
 
NUM_USERS - Static variable in class org.apache.mahout.cf.taste.hadoop.preparation.PreparePreferenceMatrixJob
 
NUM_VERTICES - Static variable in class org.apache.mahout.graph.AdjacencyMatrixJob
 
numCategories() - Method in class org.apache.mahout.classifier.AbstractVectorClassifier
Returns the number of categories for the target variable.
numCategories() - Method in class org.apache.mahout.classifier.naivebayes.AbstractNaiveBayesClassifier
 
numCategories - Variable in class org.apache.mahout.classifier.sgd.AbstractOnlineLogisticRegression
 
numCategories() - Method in class org.apache.mahout.classifier.sgd.AbstractOnlineLogisticRegression
 
numCategories() - Method in class org.apache.mahout.classifier.sgd.CrossFoldLearner
 
numCategories() - Method in class org.apache.mahout.classifier.sgd.GradientMachine
 
numCategories() - Method in class org.apache.mahout.classifier.sgd.PassiveAggressive
 
numCategories() - Method in class org.apache.mahout.clustering.ClusterClassifier
 
numChildren() - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth2.FPTree.FPNode
 
numClustersOption() - Static method in class org.apache.mahout.common.commandline.DefaultOptionCreator
Returns a default command line option for specification of numbers of clusters to create.
numCols() - Method in class org.apache.mahout.math.hadoop.DistributedRowMatrix
 
NumericalNode - Class in org.apache.mahout.classifier.df.node
Represents a node that splits using a numerical attribute
NumericalNode() - Constructor for class org.apache.mahout.classifier.df.node.NumericalNode
 
NumericalNode(int, double, Node, Node) - Constructor for class org.apache.mahout.classifier.df.node.NumericalNode
 
numFeatures() - Method in class org.apache.mahout.cf.taste.impl.recommender.svd.Factorization
 
numFeatures() - Method in class org.apache.mahout.classifier.naivebayes.NaiveBayesModel
 
numFeatures() - Method in class org.apache.mahout.classifier.naivebayes.training.AbstractThetaTrainer
 
numFeatures() - Method in class org.apache.mahout.classifier.sgd.AbstractOnlineLogisticRegression
 
numFeatures() - Method in class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression
Returns the size of the internal feature vector.
numFeatures() - Method in class org.apache.mahout.classifier.sgd.GradientMachine
 
numFeatures() - Method in class org.apache.mahout.classifier.sgd.PassiveAggressive
 
numHashFunctionsOption() - Static method in class org.apache.mahout.common.commandline.MinhashOptionCreator
Returns a default command line option for specifying the number of hash functions to be used in MinHash clustering
numHidden() - Method in class org.apache.mahout.classifier.sgd.GradientMachine
 
numItems() - Method in class org.apache.mahout.cf.taste.impl.recommender.svd.Factorization
 
numLabels() - Method in class org.apache.mahout.classifier.naivebayes.NaiveBayesModel
 
numReducersOption() - Static method in class org.apache.mahout.common.commandline.DefaultOptionCreator
Deprecated.  
numReducersOption() - Static method in class org.apache.mahout.common.commandline.MinhashOptionCreator
 
numRows() - Method in class org.apache.mahout.math.hadoop.DistributedRowMatrix
 
numSlices() - Method in class org.apache.mahout.math.hadoop.DistributedRowMatrix
 
numUsers() - Method in class org.apache.mahout.cf.taste.impl.recommender.svd.Factorization
 

O

observe(Model<VectorWritable>) - Method in class org.apache.mahout.clustering.AbstractCluster
 
observe(ClusterObservations) - Method in class org.apache.mahout.clustering.AbstractCluster
 
observe(VectorWritable) - Method in class org.apache.mahout.clustering.AbstractCluster
 
observe(VectorWritable, double) - Method in class org.apache.mahout.clustering.AbstractCluster
 
observe(Vector, double) - Method in class org.apache.mahout.clustering.AbstractCluster
 
observe(Vector) - Method in class org.apache.mahout.clustering.AbstractCluster
 
observe(VectorWritable) - Method in class org.apache.mahout.clustering.dirichlet.DirichletCluster
 
observe(VectorWritable, double) - Method in class org.apache.mahout.clustering.dirichlet.DirichletCluster
 
observe(Model<VectorWritable>) - Method in class org.apache.mahout.clustering.dirichlet.DirichletCluster
 
observe(Model<VectorWritable>[], VectorWritable) - Method in class org.apache.mahout.clustering.dirichlet.DirichletClusterer
 
observe(Vector, double) - Method in interface org.apache.mahout.clustering.GaussianAccumulator
Observe the vector
observe(O) - Method in interface org.apache.mahout.clustering.Model
Observe the given observation, retaining information about it
observe(O, double) - Method in interface org.apache.mahout.clustering.Model
Observe the given observation, retaining information about it
observe(Model<O>) - Method in interface org.apache.mahout.clustering.Model
Observe the given model, retaining information about its observations
observe(Vector, double) - Method in class org.apache.mahout.clustering.OnlineGaussianAccumulator
 
observe(Vector, double) - Method in class org.apache.mahout.clustering.RunningSumsGaussianAccumulator
 
of(A, B) - Static method in class org.apache.mahout.common.Pair
 
Omega - Class in org.apache.mahout.math.hadoop.stochasticsvd
simplistic implementation for Omega matrix in Stochastic SVD method
Omega(long, int, int) - Constructor for class org.apache.mahout.math.hadoop.stochasticsvd.Omega
 
OnlineAuc - Interface in org.apache.mahout.math.stats
Describes the generic outline of how to compute AUC.
OnlineGaussianAccumulator - Class in org.apache.mahout.clustering
An online Gaussian statistics accumulator based upon Knuth (who cites Welford) which is declared to be numerically-stable.
OnlineGaussianAccumulator() - Constructor for class org.apache.mahout.clustering.OnlineGaussianAccumulator
 
OnlineLearner - Interface in org.apache.mahout.classifier
The simplest interface for online learning algorithms.
OnlineLogisticRegression - Class in org.apache.mahout.classifier.sgd
Extends the basic on-line logistic regression learner with a specific set of learning rate annealing schedules.
OnlineLogisticRegression() - Constructor for class org.apache.mahout.classifier.sgd.OnlineLogisticRegression
 
OnlineLogisticRegression(int, int, PriorFunction) - Constructor for class org.apache.mahout.classifier.sgd.OnlineLogisticRegression
 
openStream(Path, Configuration) - Static method in class org.apache.mahout.common.HadoopUtil
 
OptIgSplit - Class in org.apache.mahout.classifier.df.split
Optimized implementation of IgSplit
This class can be used when the criterion variable is the categorical attribute.
OptIgSplit() - Constructor for class org.apache.mahout.classifier.df.split.OptIgSplit
 
optimize(double[][], double[]) - Method in class org.apache.mahout.cf.taste.impl.recommender.knn.ConjugateGradientOptimizer
Conjugate gradient optimization.
optimize(double[][], double[]) - Method in class org.apache.mahout.cf.taste.impl.recommender.knn.NonNegativeQuadraticOptimizer
Non-negative Quadratic Optimization.
optimize(double[][], double[]) - Method in interface org.apache.mahout.cf.taste.impl.recommender.knn.Optimizer
 
Optimizer - Interface in org.apache.mahout.cf.taste.impl.recommender.knn
 
OrderBasedRecommenderEvaluator - Class in org.apache.mahout.cf.taste.impl.eval
Evaluate recommender by comparing order of all raw prefs with order in recommender's output for that user.
org.apache.mahout - package org.apache.mahout
 
org.apache.mahout.cf.taste.common - package org.apache.mahout.cf.taste.common
 
org.apache.mahout.cf.taste.eval - package org.apache.mahout.cf.taste.eval
 
org.apache.mahout.cf.taste.hadoop - package org.apache.mahout.cf.taste.hadoop
 
org.apache.mahout.cf.taste.hadoop.als - package org.apache.mahout.cf.taste.hadoop.als
 
org.apache.mahout.cf.taste.hadoop.item - package org.apache.mahout.cf.taste.hadoop.item
 
org.apache.mahout.cf.taste.hadoop.preparation - package org.apache.mahout.cf.taste.hadoop.preparation
 
org.apache.mahout.cf.taste.hadoop.pseudo - package org.apache.mahout.cf.taste.hadoop.pseudo
 
org.apache.mahout.cf.taste.hadoop.similarity.item - package org.apache.mahout.cf.taste.hadoop.similarity.item
 
org.apache.mahout.cf.taste.hadoop.slopeone - package org.apache.mahout.cf.taste.hadoop.slopeone
 
org.apache.mahout.cf.taste.impl.common - package org.apache.mahout.cf.taste.impl.common
 
org.apache.mahout.cf.taste.impl.common.jdbc - package org.apache.mahout.cf.taste.impl.common.jdbc
 
org.apache.mahout.cf.taste.impl.eval - package org.apache.mahout.cf.taste.impl.eval
 
org.apache.mahout.cf.taste.impl.model - package org.apache.mahout.cf.taste.impl.model
 
org.apache.mahout.cf.taste.impl.model.file - package org.apache.mahout.cf.taste.impl.model.file
 
org.apache.mahout.cf.taste.impl.neighborhood - package org.apache.mahout.cf.taste.impl.neighborhood
 
org.apache.mahout.cf.taste.impl.recommender - package org.apache.mahout.cf.taste.impl.recommender
 
org.apache.mahout.cf.taste.impl.recommender.knn - package org.apache.mahout.cf.taste.impl.recommender.knn
 
org.apache.mahout.cf.taste.impl.recommender.slopeone - package org.apache.mahout.cf.taste.impl.recommender.slopeone
 
org.apache.mahout.cf.taste.impl.recommender.slopeone.file - package org.apache.mahout.cf.taste.impl.recommender.slopeone.file
 
org.apache.mahout.cf.taste.impl.recommender.svd - package org.apache.mahout.cf.taste.impl.recommender.svd
 
org.apache.mahout.cf.taste.impl.similarity - package org.apache.mahout.cf.taste.impl.similarity
 
org.apache.mahout.cf.taste.impl.similarity.file - package org.apache.mahout.cf.taste.impl.similarity.file
 
org.apache.mahout.cf.taste.impl.transforms - package org.apache.mahout.cf.taste.impl.transforms
 
org.apache.mahout.cf.taste.model - package org.apache.mahout.cf.taste.model
 
org.apache.mahout.cf.taste.neighborhood - package org.apache.mahout.cf.taste.neighborhood
 
org.apache.mahout.cf.taste.recommender - package org.apache.mahout.cf.taste.recommender
 
org.apache.mahout.cf.taste.recommender.slopeone - package org.apache.mahout.cf.taste.recommender.slopeone
 
org.apache.mahout.cf.taste.similarity - package org.apache.mahout.cf.taste.similarity
 
org.apache.mahout.cf.taste.transforms - package org.apache.mahout.cf.taste.transforms
 
org.apache.mahout.classifier - package org.apache.mahout.classifier
 
org.apache.mahout.classifier.bayes - package org.apache.mahout.classifier.bayes
Introduction
org.apache.mahout.classifier.bayes.mapreduce.bayes - package org.apache.mahout.classifier.bayes.mapreduce.bayes
 
org.apache.mahout.classifier.bayes.mapreduce.cbayes - package org.apache.mahout.classifier.bayes.mapreduce.cbayes
 
org.apache.mahout.classifier.bayes.mapreduce.common - package org.apache.mahout.classifier.bayes.mapreduce.common
 
org.apache.mahout.classifier.df - package org.apache.mahout.classifier.df
 
org.apache.mahout.classifier.df.builder - package org.apache.mahout.classifier.df.builder
 
org.apache.mahout.classifier.df.data - package org.apache.mahout.classifier.df.data
 
org.apache.mahout.classifier.df.data.conditions - package org.apache.mahout.classifier.df.data.conditions
 
org.apache.mahout.classifier.df.mapreduce - package org.apache.mahout.classifier.df.mapreduce
 
org.apache.mahout.classifier.df.mapreduce.inmem - package org.apache.mahout.classifier.df.mapreduce.inmem
In-memory mapreduce implementation of Random Decision Forests
org.apache.mahout.classifier.df.mapreduce.partial - package org.apache.mahout.classifier.df.mapreduce.partial
Partial-data mapreduce implementation of Random Decision Forests
org.apache.mahout.classifier.df.node - package org.apache.mahout.classifier.df.node
 
org.apache.mahout.classifier.df.ref - package org.apache.mahout.classifier.df.ref
 
org.apache.mahout.classifier.df.split - package org.apache.mahout.classifier.df.split
 
org.apache.mahout.classifier.df.tools - package org.apache.mahout.classifier.df.tools
 
org.apache.mahout.classifier.discriminative - package org.apache.mahout.classifier.discriminative
 
org.apache.mahout.classifier.evaluation - package org.apache.mahout.classifier.evaluation
 
org.apache.mahout.classifier.naivebayes - package org.apache.mahout.classifier.naivebayes
 
org.apache.mahout.classifier.naivebayes.test - package org.apache.mahout.classifier.naivebayes.test
 
org.apache.mahout.classifier.naivebayes.training - package org.apache.mahout.classifier.naivebayes.training
 
org.apache.mahout.classifier.sequencelearning.hmm - package org.apache.mahout.classifier.sequencelearning.hmm
 
org.apache.mahout.classifier.sgd - package org.apache.mahout.classifier.sgd
Implements a variety of on-line logistric regression classifiers using SGD-based algorithms.
org.apache.mahout.clustering - package org.apache.mahout.clustering
org.apache.mahout.clustering.canopy - package org.apache.mahout.clustering.canopy
 
org.apache.mahout.clustering.dirichlet - package org.apache.mahout.clustering.dirichlet
 
org.apache.mahout.clustering.dirichlet.models - package org.apache.mahout.clustering.dirichlet.models
 
org.apache.mahout.clustering.fuzzykmeans - package org.apache.mahout.clustering.fuzzykmeans
 
org.apache.mahout.clustering.kmeans - package org.apache.mahout.clustering.kmeans
This package provides an implementation of the k-means clustering algorithm.
org.apache.mahout.clustering.lda - package org.apache.mahout.clustering.lda
 
org.apache.mahout.clustering.lda.cvb - package org.apache.mahout.clustering.lda.cvb
 
org.apache.mahout.clustering.meanshift - package org.apache.mahout.clustering.meanshift
 
org.apache.mahout.clustering.minhash - package org.apache.mahout.clustering.minhash
 
org.apache.mahout.clustering.spectral.common - package org.apache.mahout.clustering.spectral.common
 
org.apache.mahout.clustering.spectral.eigencuts - package org.apache.mahout.clustering.spectral.eigencuts
 
org.apache.mahout.clustering.spectral.kmeans - package org.apache.mahout.clustering.spectral.kmeans
 
org.apache.mahout.clustering.topdown - package org.apache.mahout.clustering.topdown
 
org.apache.mahout.clustering.topdown.postprocessor - package org.apache.mahout.clustering.topdown.postprocessor
 
org.apache.mahout.common - package org.apache.mahout.common
 
org.apache.mahout.common.commandline - package org.apache.mahout.common.commandline
 
org.apache.mahout.common.distance - package org.apache.mahout.common.distance
 
org.apache.mahout.common.iterator - package org.apache.mahout.common.iterator
 
org.apache.mahout.common.iterator.sequencefile - package org.apache.mahout.common.iterator.sequencefile
 
org.apache.mahout.common.kernel - package org.apache.mahout.common.kernel
 
org.apache.mahout.common.lucene - package org.apache.mahout.common.lucene
 
org.apache.mahout.common.mapreduce - package org.apache.mahout.common.mapreduce
 
org.apache.mahout.common.nlp - package org.apache.mahout.common.nlp
 
org.apache.mahout.common.parameters - package org.apache.mahout.common.parameters
 
org.apache.mahout.driver - package org.apache.mahout.driver
 
org.apache.mahout.ep - package org.apache.mahout.ep
Provides basic evolutionary optimization using recorded-step mutation.
org.apache.mahout.fpm.pfpgrowth - package org.apache.mahout.fpm.pfpgrowth
MapReduce (parallel) implementation of FP Growth Algorithm for frequent Itemset Mining
org.apache.mahout.fpm.pfpgrowth.convertors - package org.apache.mahout.fpm.pfpgrowth.convertors
 
org.apache.mahout.fpm.pfpgrowth.convertors.integer - package org.apache.mahout.fpm.pfpgrowth.convertors.integer
 
org.apache.mahout.fpm.pfpgrowth.convertors.string - package org.apache.mahout.fpm.pfpgrowth.convertors.string
 
org.apache.mahout.fpm.pfpgrowth.fpgrowth - package org.apache.mahout.fpm.pfpgrowth.fpgrowth
 
org.apache.mahout.fpm.pfpgrowth.fpgrowth2 - package org.apache.mahout.fpm.pfpgrowth.fpgrowth2
 
org.apache.mahout.ga.watchmaker - package org.apache.mahout.ga.watchmaker
 
org.apache.mahout.graph - package org.apache.mahout.graph
 
org.apache.mahout.graph.linkanalysis - package org.apache.mahout.graph.linkanalysis
 
org.apache.mahout.math - package org.apache.mahout.math
 
org.apache.mahout.math.hadoop - package org.apache.mahout.math.hadoop
 
org.apache.mahout.math.hadoop.decomposer - package org.apache.mahout.math.hadoop.decomposer
 
org.apache.mahout.math.hadoop.similarity - package org.apache.mahout.math.hadoop.similarity
 
org.apache.mahout.math.hadoop.similarity.cooccurrence - package org.apache.mahout.math.hadoop.similarity.cooccurrence
 
org.apache.mahout.math.hadoop.similarity.cooccurrence.measures - package org.apache.mahout.math.hadoop.similarity.cooccurrence.measures
 
org.apache.mahout.math.hadoop.solver - package org.apache.mahout.math.hadoop.solver
 
org.apache.mahout.math.hadoop.stats - package org.apache.mahout.math.hadoop.stats
 
org.apache.mahout.math.hadoop.stochasticsvd - package org.apache.mahout.math.hadoop.stochasticsvd
 
org.apache.mahout.math.hadoop.stochasticsvd.qr - package org.apache.mahout.math.hadoop.stochasticsvd.qr
 
org.apache.mahout.math.ssvd - package org.apache.mahout.math.ssvd
 
org.apache.mahout.math.stats - package org.apache.mahout.math.stats
 
org.apache.mahout.math.stats.entropy - package org.apache.mahout.math.stats.entropy
 
org.apache.mahout.vectorizer - package org.apache.mahout.vectorizer
 
org.apache.mahout.vectorizer.collocations.llr - package org.apache.mahout.vectorizer.collocations.llr
 
org.apache.mahout.vectorizer.common - package org.apache.mahout.vectorizer.common
 
org.apache.mahout.vectorizer.document - package org.apache.mahout.vectorizer.document
 
org.apache.mahout.vectorizer.encoders - package org.apache.mahout.vectorizer.encoders
 
org.apache.mahout.vectorizer.pruner - package org.apache.mahout.vectorizer.pruner
 
org.apache.mahout.vectorizer.term - package org.apache.mahout.vectorizer.term
 
org.apache.mahout.vectorizer.tfidf - package org.apache.mahout.vectorizer.tfidf
 
orthonormalizeColumns(Matrix) - Static method in class org.apache.mahout.math.hadoop.stochasticsvd.qr.GramSchmidt
 
OUT_DIR_SUFFIX - Static variable in class org.apache.mahout.vectorizer.HighDFWordsPruner
 
OUT_TYPE_KEY - Static variable in class org.apache.mahout.math.hadoop.similarity.VectorDistanceSimilarityJob
 
OUTPUT - Static variable in class org.apache.mahout.fpm.pfpgrowth.PFPGrowth
 
OUTPUT_BBT - Static variable in class org.apache.mahout.math.hadoop.stochasticsvd.BtJob
 
OUTPUT_BT - Static variable in class org.apache.mahout.math.hadoop.stochasticsvd.BtJob
 
OUTPUT_OPTION - Static variable in class org.apache.mahout.common.commandline.DefaultOptionCreator
 
OUTPUT_Q - Static variable in class org.apache.mahout.math.hadoop.stochasticsvd.BtJob
 
OUTPUT_QHAT - Static variable in class org.apache.mahout.math.hadoop.stochasticsvd.QJob
 
OUTPUT_RHAT - Static variable in class org.apache.mahout.math.hadoop.stochasticsvd.QJob
 
OUTPUT_VECTOR_DIMENSION - Static variable in class org.apache.mahout.math.hadoop.TimesSquaredJob
 
OUTPUT_VECTOR_FILENAME - Static variable in class org.apache.mahout.math.hadoop.TimesSquaredJob
 
OUTPUT_YtY - Static variable in class org.apache.mahout.math.hadoop.stochasticsvd.YtYJob
 
outputOption() - Static method in class org.apache.mahout.common.commandline.DefaultOptionCreator
Returns a default command line option for output directory specification.
outputPointWithClusterInfo(Vector, Iterable<Cluster>, Mapper<?, ?, IntWritable, WeightedPropertyVectorWritable>.Context) - Method in class org.apache.mahout.clustering.kmeans.KMeansClusterer
 
OutputUtils - Class in org.apache.mahout.ga.watchmaker
Utility Class that deals with the output.
OVERSHOOT_MULTIPLIER - Static variable in class org.apache.mahout.clustering.spectral.eigencuts.EigencutsDriver
 
OVERSHOOT_MULTIPLIER - Static variable in class org.apache.mahout.clustering.spectral.kmeans.SpectralKMeansDriver
 
OVERWRITE_OPTION - Static variable in class org.apache.mahout.common.commandline.DefaultOptionCreator
 
overwriteOption() - Static method in class org.apache.mahout.common.commandline.DefaultOptionCreator
Returns a default command line option for output directory overwriting.

P

PageRankJob - Class in org.apache.mahout.graph.linkanalysis
Distributed computation of the PageRank a directed graph
PageRankJob() - Constructor for class org.apache.mahout.graph.linkanalysis.PageRankJob
 
Pair<A,B> - Class in org.apache.mahout.common
A simple (ordered) pair of two objects.
Pair(A, B) - Constructor for class org.apache.mahout.common.Pair
 
PARALLEL_COUNTING - Static variable in class org.apache.mahout.fpm.pfpgrowth.PFPGrowth
 
ParallelALSFactorizationJob - Class in org.apache.mahout.cf.taste.hadoop.als
MapReduce implementation of the two factorization algorithms described in
ParallelALSFactorizationJob() - Constructor for class org.apache.mahout.cf.taste.hadoop.als.ParallelALSFactorizationJob
 
ParallelCountingMapper - Class in org.apache.mahout.fpm.pfpgrowth
maps all items in a particular transaction like the way it is done in Hadoop WordCount example
ParallelCountingMapper() - Constructor for class org.apache.mahout.fpm.pfpgrowth.ParallelCountingMapper
 
ParallelCountingReducer - Class in org.apache.mahout.fpm.pfpgrowth
sums up the item count and output the item and the count This can also be used as a local Combiner.
ParallelCountingReducer() - Constructor for class org.apache.mahout.fpm.pfpgrowth.ParallelCountingReducer
 
parallelDo(EvolutionaryProcess.Function<Payload<U>>) - Method in class org.apache.mahout.ep.EvolutionaryProcess
Execute an operation on all of the members of the population with many threads.
ParallelFPGrowthCombiner - Class in org.apache.mahout.fpm.pfpgrowth
takes each group of dependent transactions and\ compacts it in a TransactionTree structure
ParallelFPGrowthCombiner() - Constructor for class org.apache.mahout.fpm.pfpgrowth.ParallelFPGrowthCombiner
 
ParallelFPGrowthMapper - Class in org.apache.mahout.fpm.pfpgrowth
maps each transaction to all unique items groups in the transaction.
ParallelFPGrowthMapper() - Constructor for class org.apache.mahout.fpm.pfpgrowth.ParallelFPGrowthMapper
 
ParallelFPGrowthReducer - Class in org.apache.mahout.fpm.pfpgrowth
takes each group of transactions and runs Vanilla FPGrowth on it and outputs the the Top K frequent Patterns for each group.
ParallelFPGrowthReducer() - Constructor for class org.apache.mahout.fpm.pfpgrowth.ParallelFPGrowthReducer
 
Parameter<T> - Interface in org.apache.mahout.common.parameters
An accessor to a parameters in the job.
Parametered - Interface in org.apache.mahout.common.parameters
Meta information and accessors for configuring a job.
Parametered.ParameteredGeneralizations - Class in org.apache.mahout.common.parameters
"multiple inheritance"
Parameters - Class in org.apache.mahout.common
 
Parameters() - Constructor for class org.apache.mahout.common.Parameters
 
Parameters(String) - Constructor for class org.apache.mahout.common.Parameters
 
Parameters(Map<String, String>) - Constructor for class org.apache.mahout.common.Parameters
 
parent(int) - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.FPTree
 
parent() - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth2.FPTree.FPNode
 
parseArguments(String[]) - Method in class org.apache.mahout.common.AbstractJob
Parse the arguments specified based on the options defined using the various addOption methods.
parseDescriptor(CharSequence) - Static method in class org.apache.mahout.classifier.df.data.DescriptorUtils
Parses a descriptor string and generates the corresponding array of Attributes
parseDirectories(CommandLine) - Method in class org.apache.mahout.common.AbstractJob
Obtain input and output directories from command-line options or hadoop properties.
parseElement(ResultSet) - Method in class org.apache.mahout.cf.taste.impl.common.jdbc.ResultSetIterator
 
parseMetaData(CharSequence) - Static method in class org.apache.mahout.math.hadoop.decomposer.EigenVector
 
parseMetaData() - Method in class org.apache.mahout.math.hadoop.decomposer.EigenVector
 
parseOutput(Job) - Method in class org.apache.mahout.classifier.df.mapreduce.Builder
Parse the output files to extract the trees and pass the predictions to the callback
parseOutput(Job) - Method in class org.apache.mahout.classifier.df.mapreduce.inmem.InMemBuilder
 
parseOutput(Job) - Method in class org.apache.mahout.classifier.df.mapreduce.partial.PartialBuilder
 
parseParams(String) - Static method in class org.apache.mahout.common.Parameters
 
partFilter() - Static method in class org.apache.mahout.common.iterator.sequencefile.PathFilters
 
PartialBuilder - Class in org.apache.mahout.classifier.df.mapreduce.partial
Builds a random forest using partial data.
PartialBuilder(TreeBuilder, Path, Path, Long) - Constructor for class org.apache.mahout.classifier.df.mapreduce.partial.PartialBuilder
 
PartialBuilder(TreeBuilder, Path, Path, Long, Configuration) - Constructor for class org.apache.mahout.classifier.df.mapreduce.partial.PartialBuilder
 
PartialMultiplyMapper - Class in org.apache.mahout.cf.taste.hadoop.item
maps similar items and their preference values per user
PartialMultiplyMapper() - Constructor for class org.apache.mahout.cf.taste.hadoop.item.PartialMultiplyMapper
 
PartialRowEmitter - Interface in org.apache.mahout.math.hadoop.stochasticsvd
This is part of SSVD prototype code
PartialVectorMerger - Class in org.apache.mahout.vectorizer.common
This class groups a set of input vectors.
PartialVectorMergeReducer - Class in org.apache.mahout.vectorizer.common
Merges partial vectors in to a full sparse vector
PartialVectorMergeReducer() - Constructor for class org.apache.mahout.vectorizer.common.PartialVectorMergeReducer
 
partition() - Method in class org.apache.mahout.classifier.df.mapreduce.partial.TreeID
Data partition (InputSplit's index) that was used to grow the tree
PassiveAggressive - Class in org.apache.mahout.classifier.sgd
Online passive aggressive learner that tries to minimize the label ranking hinge loss.
PassiveAggressive(int, int) - Constructor for class org.apache.mahout.classifier.sgd.PassiveAggressive
 
PathDirectory - Class in org.apache.mahout.clustering.topdown
Contains list of all internal paths used in top down clustering.
PathFilters - Class in org.apache.mahout.common.iterator.sequencefile
Supplies some useful and repeatedly-used instances of PathFilter.
PathParameter - Class in org.apache.mahout.common.parameters
 
PathParameter(String, String, Configuration, Path, String) - Constructor for class org.apache.mahout.common.parameters.PathParameter
 
PathType - Enum in org.apache.mahout.common.iterator.sequencefile
Used by SequenceFileDirIterable and the like to select whether the input path specifies a directory to list, or a glob pattern.
Pattern - Class in org.apache.mahout.fpm.pfpgrowth.fpgrowth
A in FPGrowth is a list of items (here int) and the support(the number of times the pattern is seen in the dataset)
Pattern() - Constructor for class org.apache.mahout.fpm.pfpgrowth.fpgrowth.Pattern
 
Payload<T> - Interface in org.apache.mahout.ep
Payloads for evolutionary state must be copyable and updatable.
pdf(VectorWritable) - Method in class org.apache.mahout.clustering.dirichlet.DirichletCluster
 
pdf(VectorWritable) - Method in class org.apache.mahout.clustering.dirichlet.models.GaussianCluster
 
pdf(VectorWritable) - Method in class org.apache.mahout.clustering.DistanceMeasureCluster
 
pdf(VectorWritable) - Method in class org.apache.mahout.clustering.fuzzykmeans.SoftCluster
 
pdf(VectorWritable) - Method in class org.apache.mahout.clustering.meanshift.MeanShiftCanopy
 
pdf(O) - Method in interface org.apache.mahout.clustering.Model
Return the probability that the observation is described by this model
PearsonCorrelationSimilarity - Class in org.apache.mahout.cf.taste.impl.similarity
An implementation of the Pearson correlation.
PearsonCorrelationSimilarity(DataModel) - Constructor for class org.apache.mahout.cf.taste.impl.similarity.PearsonCorrelationSimilarity
 
PearsonCorrelationSimilarity(DataModel, Weighting) - Constructor for class org.apache.mahout.cf.taste.impl.similarity.PearsonCorrelationSimilarity
 
PearsonCorrelationSimilarity - Class in org.apache.mahout.math.hadoop.similarity.cooccurrence.measures
 
PearsonCorrelationSimilarity() - Constructor for class org.apache.mahout.math.hadoop.similarity.cooccurrence.measures.PearsonCorrelationSimilarity
 
peek() - Method in class org.apache.mahout.cf.taste.impl.common.LongPrimitiveArrayIterator
 
peek() - Method in interface org.apache.mahout.cf.taste.impl.common.LongPrimitiveIterator
 
peek() - Method in class org.apache.mahout.cf.taste.impl.common.SamplingLongPrimitiveIterator
 
percentCorrect() - Method in class org.apache.mahout.classifier.sgd.CrossFoldLearner
 
PerceptronTrainer - Class in org.apache.mahout.classifier.discriminative
Implements training according to the perceptron update rule.
PerceptronTrainer(int, double, double, double, double) - Constructor for class org.apache.mahout.classifier.discriminative.PerceptronTrainer
 
performEigenDecomposition(Configuration, DistributedRowMatrix, LanczosState, int, int, Path) - Static method in class org.apache.mahout.clustering.spectral.eigencuts.EigencutsDriver
Does most of the heavy lifting in setting up Paths, configuring return values, and generally performing the tedious administrative tasks involved in an eigen-decomposition and running the verifier
perplexity(Vector, Vector) - Method in class org.apache.mahout.clustering.lda.cvb.TopicModel
sum_x sum_a (c_ai * log(p(x|i) * p(a|x)))
perplexityPath(Path, int) - Static method in class org.apache.mahout.clustering.lda.cvb.CVB0Driver
 
persist(Path) - Method in class org.apache.mahout.clustering.lda.cvb.ModelTrainer
 
persist(Path, boolean) - Method in class org.apache.mahout.clustering.lda.cvb.TopicModel
 
PersistenceStrategy - Interface in org.apache.mahout.cf.taste.impl.recommender.svd
Provides storage for Factorizations
persistVector(Path, int, Vector) - Method in class org.apache.mahout.math.hadoop.decomposer.HdfsBackedLanczosState
 
perTermLearningRate(int) - Method in class org.apache.mahout.classifier.sgd.AbstractOnlineLogisticRegression
 
perTermLearningRate(int) - Method in class org.apache.mahout.classifier.sgd.OnlineLogisticRegression
 
PFP_PARAMETERS - Static variable in class org.apache.mahout.fpm.pfpgrowth.PFPGrowth
 
PFPGrowth - Class in org.apache.mahout.fpm.pfpgrowth
Parallel FP Growth Driver Class.
phi(int, int) - Method in class org.apache.mahout.clustering.lda.LDAInference.InferredDocument
 
PlusAnonymousUserDataModel - Class in org.apache.mahout.cf.taste.impl.model
This DataModel decorator class is useful in a situation where you wish to recommend to a user that doesn't really exist yet in your actual DataModel.
PlusAnonymousUserDataModel(DataModel) - Constructor for class org.apache.mahout.cf.taste.impl.model.PlusAnonymousUserDataModel
 
plusBlock(SparseRowBlockWritable) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.SparseRowBlockWritable
pluses one block into another.
plusRow(int, Vector) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.SparseRowBlockWritable
 
PolymorphicWritable - Class in org.apache.mahout.classifier.sgd
Utilities that write a class name and then serialize using writables.
POST_PROCESS_DIRECTORY - Static variable in class org.apache.mahout.clustering.topdown.PathDirectory
 
predict(HmmModel, int) - Static method in class org.apache.mahout.classifier.sequencelearning.hmm.HmmEvaluator
Predict a sequence of steps output states for the given HMM model
predict(HmmModel, int, long) - Static method in class org.apache.mahout.classifier.sequencelearning.hmm.HmmEvaluator
Predict a sequence of steps output states for the given HMM model using the given seed for probabilistic experiments
predictTrace(Node, Data, String[]) - Static method in class org.apache.mahout.classifier.df.tools.TreeVisualizer
Predict trace to String
predictTracePrint(Node, Data, String[]) - Static method in class org.apache.mahout.classifier.df.tools.TreeVisualizer
Print predict trace
PrefAndSimilarityColumnWritable - Class in org.apache.mahout.cf.taste.hadoop.item
 
PrefAndSimilarityColumnWritable() - Constructor for class org.apache.mahout.cf.taste.hadoop.item.PrefAndSimilarityColumnWritable
 
PrefAndSimilarityColumnWritable(float, Vector) - Constructor for class org.apache.mahout.cf.taste.hadoop.item.PrefAndSimilarityColumnWritable
 
Preference - Interface in org.apache.mahout.cf.taste.model
A encapsulates an item and a preference value, which indicates the strength of the preference for it.
PreferenceArray - Interface in org.apache.mahout.cf.taste.model
An alternate representation of an array of Preference.
PreferenceInferrer - Interface in org.apache.mahout.cf.taste.similarity
Implementations of this interface compute an inferred preference for a user and an item that the user has not expressed any preference for.
PreferenceTransform - Interface in org.apache.mahout.cf.taste.transforms
Implementations encapsulate a transform on a Preference's value.
PreferredItemsNeighborhoodCandidateItemsStrategy - Class in org.apache.mahout.cf.taste.impl.recommender
 
PreferredItemsNeighborhoodCandidateItemsStrategy() - Constructor for class org.apache.mahout.cf.taste.impl.recommender.PreferredItemsNeighborhoodCandidateItemsStrategy
 
prefix() - Method in class org.apache.mahout.common.parameters.AbstractParameter
 
prefix() - Method in interface org.apache.mahout.common.parameters.Parameter
 
prepareJob(Path, Path, Class<? extends InputFormat>, Class<? extends Mapper>, Class<? extends Writable>, Class<? extends Writable>, Class<? extends OutputFormat>) - Method in class org.apache.mahout.common.AbstractJob
 
prepareJob(Path, Path, Class<? extends Mapper>, Class<? extends Writable>, Class<? extends Writable>, Class<? extends Reducer>, Class<? extends Writable>, Class<? extends Writable>) - Method in class org.apache.mahout.common.AbstractJob
 
prepareJob(Path, Path, Class<? extends InputFormat>, Class<? extends Mapper>, Class<? extends Writable>, Class<? extends Writable>, Class<? extends Reducer>, Class<? extends Writable>, Class<? extends Writable>, Class<? extends OutputFormat>) - Method in class org.apache.mahout.common.AbstractJob
 
prepareJob(Path, Path, Class<? extends InputFormat>, Class<? extends Mapper>, Class<? extends Writable>, Class<? extends Writable>, Class<? extends OutputFormat>, Configuration) - Static method in class org.apache.mahout.common.HadoopUtil
Create a map-only Hadoop Job out of the passed in parameters.
prepareJob(Path, Path, Class<? extends InputFormat>, Class<? extends Mapper>, Class<? extends Writable>, Class<? extends Writable>, Class<? extends Reducer>, Class<? extends Writable>, Class<? extends Writable>, Class<? extends OutputFormat>, Configuration) - Static method in class org.apache.mahout.common.HadoopUtil
Create a map and reduce Hadoop job.
PreparePreferenceMatrixJob - Class in org.apache.mahout.cf.taste.hadoop.preparation
 
PreparePreferenceMatrixJob() - Constructor for class org.apache.mahout.cf.taste.hadoop.preparation.PreparePreferenceMatrixJob
 
print(String, String, String[]) - Static method in class org.apache.mahout.classifier.df.tools.ForestVisualizer
Print Decision Forest
print(Node, Dataset, String[]) - Static method in class org.apache.mahout.classifier.df.tools.TreeVisualizer
Print Decision tree
print() - Method in class org.apache.mahout.common.Parameters
 
printHelp(Group) - Static method in class org.apache.mahout.common.CommandLineUtil
 
printHelpWithGenericOptions(Group) - Static method in class org.apache.mahout.common.CommandLineUtil
Print the options supported by GenericOptionsParser.
printHelpWithGenericOptions(Group, OptionException) - Static method in class org.apache.mahout.common.CommandLineUtil
 
prior - Variable in class org.apache.mahout.classifier.sgd.AbstractOnlineLogisticRegression
 
PriorFunction - Interface in org.apache.mahout.classifier.sgd
A prior is used to regularize the learning algorithm.
process() - Method in class org.apache.mahout.clustering.topdown.postprocessor.ClusterOutputPostProcessor
This method takes the clustered points output by the clustering algorithms as input and writes them into their respective clusters.
processFile(FileLineIterator, FastByIDMap<?>, FastByIDMap<FastByIDMap<Long>>, boolean) - Method in class org.apache.mahout.cf.taste.impl.model.file.FileDataModel
 
processFileWithoutID(FileLineIterator, FastByIDMap<FastIDSet>, FastByIDMap<FastByIDMap<Long>>) - Method in class org.apache.mahout.cf.taste.impl.model.file.FileDataModel
 
processLine(String, FastByIDMap<?>, FastByIDMap<FastByIDMap<Long>>, boolean) - Method in class org.apache.mahout.cf.taste.impl.model.file.FileDataModel
Reads one line from the input file and adds the data to a FastByIDMap data structure which maps user IDs to preferences.
processLine(String, Vector) - Method in class org.apache.mahout.classifier.sgd.CsvRecordFactory
Decodes a single line of csv data and records the target and predictor variables in a record.
processLine(CharSequence, Vector, boolean) - Method in class org.apache.mahout.classifier.sgd.CsvRecordFactory
Decodes a single line of csv data and records the target(if retrunTarget is true) and predictor variables in a record.
processLine(String, Vector) - Method in interface org.apache.mahout.classifier.sgd.RecordFactory
 
processLineWithoutID(String, FastByIDMap<FastIDSet>, FastByIDMap<FastByIDMap<Long>>) - Method in class org.apache.mahout.cf.taste.impl.model.file.FileDataModel
 
processOneEstimate(float, Preference) - Method in class org.apache.mahout.cf.taste.impl.eval.AbstractDifferenceRecommenderEvaluator
 
processOneEstimate(float, Preference) - Method in class org.apache.mahout.cf.taste.impl.eval.AverageAbsoluteDifferenceRecommenderEvaluator
 
processOneEstimate(float, Preference) - Method in class org.apache.mahout.cf.taste.impl.eval.RMSRecommenderEvaluator
 
processOtherUser(long, FastIDSet, FastByIDMap<PreferenceArray>, long, DataModel) - Method in interface org.apache.mahout.cf.taste.eval.RelevantItemsDataSplitter
Adds a single user and all their preferences to the training model.
processOtherUser(long, FastIDSet, FastByIDMap<PreferenceArray>, long, DataModel) - Method in class org.apache.mahout.cf.taste.impl.eval.GenericRelevantItemsDataSplitter
 
processOutput(JobContext, Path, TreeID[], Node[]) - Static method in class org.apache.mahout.classifier.df.mapreduce.partial.PartialBuilder
Processes the output from the output path.
processSubgram(Iterator<Gram>, Reducer<GramKey, Gram, Gram, Gram>.Context) - Method in class org.apache.mahout.vectorizer.collocations.llr.CollocReducer
Sum frequencies for subgram, ngrams and deliver ngram, subgram pairs to the collector.
processTfIdf(Path, Path, Configuration, Pair<Long[], List<Path>>, int, long, float, boolean, boolean, boolean, int) - Static method in class org.apache.mahout.vectorizer.tfidf.TFIDFConverter
Create Term Frequency-Inverse Document Frequency (Tf-Idf) Vectors from the input set of vectors in SequenceFile format.
processUnigram(Iterator<Gram>, Reducer<GramKey, Gram, Gram, Gram>.Context) - Method in class org.apache.mahout.vectorizer.collocations.llr.CollocReducer
Sum frequencies for unigrams and deliver to the collector
PROP_AROWBLOCK_SIZE - Static variable in class org.apache.mahout.math.hadoop.stochasticsvd.QJob
 
PROP_AROWBLOCK_SIZE - Static variable in class org.apache.mahout.math.hadoop.stochasticsvd.qr.QRFirstStep
 
PROP_BT_BROADCAST - Static variable in class org.apache.mahout.math.hadoop.stochasticsvd.ABtDenseOutJob
 
PROP_BT_BROADCAST - Static variable in class org.apache.mahout.math.hadoop.stochasticsvd.ABtJob
 
PROP_BT_PATH - Static variable in class org.apache.mahout.math.hadoop.stochasticsvd.ABtDenseOutJob
 
PROP_BT_PATH - Static variable in class org.apache.mahout.math.hadoop.stochasticsvd.ABtJob
 
PROP_K - Static variable in class org.apache.mahout.math.hadoop.stochasticsvd.QJob
 
PROP_K - Static variable in class org.apache.mahout.math.hadoop.stochasticsvd.qr.QRFirstStep
 
PROP_K - Static variable in class org.apache.mahout.math.hadoop.stochasticsvd.YtYJob
 
PROP_OMEGA_SEED - Static variable in class org.apache.mahout.math.hadoop.stochasticsvd.QJob
 
PROP_OMEGA_SEED - Static variable in class org.apache.mahout.math.hadoop.stochasticsvd.YtYJob
 
PROP_OUPTUT_BBT_PRODUCTS - Static variable in class org.apache.mahout.math.hadoop.stochasticsvd.BtJob
 
PROP_OUTER_PROD_BLOCK_HEIGHT - Static variable in class org.apache.mahout.math.hadoop.stochasticsvd.BtJob
 
PROP_P - Static variable in class org.apache.mahout.math.hadoop.stochasticsvd.QJob
 
PROP_P - Static variable in class org.apache.mahout.math.hadoop.stochasticsvd.qr.QRFirstStep
 
PROP_P - Static variable in class org.apache.mahout.math.hadoop.stochasticsvd.YtYJob
 
PROP_QJOB_PATH - Static variable in class org.apache.mahout.math.hadoop.stochasticsvd.BtJob
 
PROP_RHAT_BROADCAST - Static variable in class org.apache.mahout.math.hadoop.stochasticsvd.BtJob
 
PrunedPartialVectorMergeReducer - Class in org.apache.mahout.vectorizer.pruner
 
PrunedPartialVectorMergeReducer() - Constructor for class org.apache.mahout.vectorizer.pruner.PrunedPartialVectorMergeReducer
 
pruneVectors(Path, Path, Path, long, Configuration, Pair<Long[], List<Path>>, float, boolean, int) - Static method in class org.apache.mahout.vectorizer.HighDFWordsPruner
 
put(long, V) - Method in class org.apache.mahout.cf.taste.impl.common.FastByIDMap
 
put(K, V) - Method in class org.apache.mahout.cf.taste.impl.common.FastMap
 
putAll(Map<? extends K, ? extends V>) - Method in class org.apache.mahout.cf.taste.impl.common.FastMap
 
putCount(String, String, int) - Method in class org.apache.mahout.classifier.ConfusionMatrix
 

Q

qhatCollector - Variable in class org.apache.mahout.math.hadoop.stochasticsvd.ABtDenseOutJob.QRReducer
 
qhatCollector - Variable in class org.apache.mahout.math.hadoop.stochasticsvd.ABtJob.QRReducer
 
QJob - Class in org.apache.mahout.math.hadoop.stochasticsvd
Compute first level of QHat-transpose blocks.
QJob.QMapper - Class in org.apache.mahout.math.hadoop.stochasticsvd
 
QJob.QMapper() - Constructor for class org.apache.mahout.math.hadoop.stochasticsvd.QJob.QMapper
 
qr - Variable in class org.apache.mahout.math.hadoop.stochasticsvd.ABtDenseOutJob.QRReducer
 
qr - Variable in class org.apache.mahout.math.hadoop.stochasticsvd.ABtJob.QRReducer
 
QRFirstStep - Class in org.apache.mahout.math.hadoop.stochasticsvd.qr
QR first step without MR abstractions and doing it just in terms of iterators and collectors.
QRFirstStep(Configuration, OutputCollector<? super Writable, ? super DenseBlockWritable>, OutputCollector<? super Writable, ? super VectorWritable>) - Constructor for class org.apache.mahout.math.hadoop.stochasticsvd.qr.QRFirstStep
 
QRLastStep - Class in org.apache.mahout.math.hadoop.stochasticsvd.qr
Second/last step of QR iterations.
QRLastStep(Iterator<DenseBlockWritable>, Iterator<VectorWritable>, int) - Constructor for class org.apache.mahout.math.hadoop.stochasticsvd.qr.QRLastStep
 
queueingComparator(Comparator<? super T>) - Method in class org.apache.mahout.cf.taste.common.MinK
 
queueingComparator(Comparator<? super T>) - Method in class org.apache.mahout.cf.taste.common.TopK
 
quietClose(ResultSet) - Static method in class org.apache.mahout.common.IOUtils
 
quietClose(Statement) - Static method in class org.apache.mahout.common.IOUtils
 
quietClose(Connection) - Static method in class org.apache.mahout.common.IOUtils
 
quietClose(ResultSet, Statement, Connection) - Static method in class org.apache.mahout.common.IOUtils
Closes a ResultSet, Statement and Connection (if not null) and logs (but does not rethrow) any resulting SQLException.

R

RANDOM_SEED - Static variable in class org.apache.mahout.clustering.lda.cvb.CVB0Driver
 
randomAttributes(Random, boolean[], int) - Static method in class org.apache.mahout.classifier.df.builder.DefaultTreeBuilder
Randomly selects m attributes to consider for split, excludes IGNORED and LABEL attributes
RandomRecommender - Class in org.apache.mahout.cf.taste.impl.recommender
Produces random recommendations and preference estimates.
RandomRecommender(DataModel) - Constructor for class org.apache.mahout.cf.taste.impl.recommender.RandomRecommender
 
RandomSeedGenerator - Class in org.apache.mahout.clustering.kmeans
Given an Input Path containing a SequenceFile, randomly select k vectors and write them to the output file as a Cluster representing the initial centroid to use.
RandomSequenceGenerator - Class in org.apache.mahout.classifier.sequencelearning.hmm
Command-line tool for generating random sequences by given HMM
RandomWalkWithRestartJob - Class in org.apache.mahout.graph.linkanalysis
Distributed computation of the proximities of vertices to a source vertex in a directed graph
RandomWalkWithRestartJob() - Constructor for class org.apache.mahout.graph.linkanalysis.RandomWalkWithRestartJob
 
RankingGradient - Class in org.apache.mahout.classifier.sgd
Uses the difference between this instance and recent history to get a gradient that optimizes ranking performance.
RankingGradient(int) - Constructor for class org.apache.mahout.classifier.sgd.RankingGradient
 
RATING_MATRIX - Static variable in class org.apache.mahout.cf.taste.hadoop.preparation.PreparePreferenceMatrixJob
 
RATING_SHIFT - Static variable in class org.apache.mahout.cf.taste.hadoop.ToEntityPrefsMapper
 
ratingVector(PreferenceArray) - Method in class org.apache.mahout.cf.taste.impl.recommender.svd.ALSWRFactorizer
 
RAW_EIGENVECTORS - Static variable in class org.apache.mahout.math.hadoop.decomposer.DistributedLanczosSolver
 
rBeta(double, double) - Static method in class org.apache.mahout.clustering.dirichlet.UncommonDistributions
Returns a random sample from a beta distribution with the given shapes
rBeta(int, double, double) - Static method in class org.apache.mahout.clustering.dirichlet.UncommonDistributions
Returns a vector of random samples from a beta distribution with the given shapes
rBinomial(int, double) - Static method in class org.apache.mahout.clustering.dirichlet.UncommonDistributions
Returns an integer sampled according to this distribution.
rChisq(double) - Static method in class org.apache.mahout.clustering.dirichlet.UncommonDistributions
Return a random sample from the chi-squared (chi^2) distribution with df degrees of freedom.
rDirichlet(Vector, double) - Static method in class org.apache.mahout.clustering.dirichlet.UncommonDistributions
Sample from a Dirichlet distribution, returning a vector of probabilities using a stick-breaking algorithm
read(DataInput) - Static method in class org.apache.mahout.classifier.df.data.Dataset
 
read(DataInput) - Static method in class org.apache.mahout.classifier.df.mapreduce.inmem.InMemInputFormat.InMemInputSplit
 
read(DataInput) - Static method in class org.apache.mahout.classifier.df.node.Node
 
read(DataInput, Class<? extends T>) - Static method in class org.apache.mahout.classifier.sgd.PolymorphicWritable
 
read(Path, Configuration) - Static method in class org.apache.mahout.math.hadoop.similarity.cooccurrence.Vectors
 
read(Configuration, Path...) - Static method in class org.apache.mahout.math.MatrixUtils
 
read(DataInput) - Static method in class org.apache.mahout.math.MultiLabelVectorWritable
 
readAsIntMap(Path, Configuration) - Static method in class org.apache.mahout.math.hadoop.similarity.cooccurrence.Vectors
 
readAsIntMap(DataInput) - Static method in class org.apache.mahout.math.hadoop.similarity.cooccurrence.Vectors
 
readBinary(DataInput) - Static method in class org.apache.mahout.cf.taste.impl.recommender.svd.FilePersistenceStrategy
 
readBinary(InputStream, Class<T>) - Static method in class org.apache.mahout.classifier.sgd.ModelSerializer
 
readClassifier(Path) - Static method in class org.apache.mahout.clustering.ClusterIterator
 
readDictionary(Configuration, Path...) - Static method in class org.apache.mahout.math.MatrixUtils
 
readDoubleArray(DataInput) - Static method in class org.apache.mahout.classifier.df.DFUtils
Reads a double[] from a DataInput
readerToDocument(Analyzer, Reader) - Static method in class org.apache.mahout.classifier.BayesFileFormatter
Convert a Reader to a vector
readFields(DataInput) - Method in class org.apache.mahout.cf.taste.hadoop.EntityCountWritable
 
readFields(DataInput) - Method in class org.apache.mahout.cf.taste.hadoop.EntityEntityWritable
 
readFields(DataInput) - Method in class org.apache.mahout.cf.taste.hadoop.EntityPrefWritable
 
readFields(DataInput) - Method in class org.apache.mahout.cf.taste.hadoop.item.PrefAndSimilarityColumnWritable
 
readFields(DataInput) - Method in class org.apache.mahout.cf.taste.hadoop.item.VectorAndPrefsWritable
 
readFields(DataInput) - Method in class org.apache.mahout.cf.taste.hadoop.item.VectorOrPrefWritable
 
readFields(DataInput) - Method in class org.apache.mahout.cf.taste.hadoop.RecommendedItemsWritable
 
readFields(DataInput) - Method in class org.apache.mahout.cf.taste.hadoop.slopeone.FullRunningAverageAndStdDevWritable
 
readFields(DataInput) - Method in class org.apache.mahout.classifier.df.data.Dataset
 
readFields(DataInput) - Method in class org.apache.mahout.classifier.df.DecisionForest
Reads the trees from the input and adds them to the existing trees
readFields(DataInput) - Method in class org.apache.mahout.classifier.df.mapreduce.inmem.InMemInputFormat.InMemInputSplit
 
readFields(DataInput) - Method in class org.apache.mahout.classifier.df.mapreduce.MapredOutput
 
readFields(DataInput) - Method in class org.apache.mahout.classifier.df.node.CategoricalNode
 
readFields(DataInput) - Method in class org.apache.mahout.classifier.df.node.Leaf
 
readFields(DataInput) - Method in class org.apache.mahout.classifier.df.node.NumericalNode
 
readFields(DataInput) - Method in class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression
 
readFields(DataInput) - Method in class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression.TrainingExample
 
readFields(DataInput) - Method in class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression.Wrapper
 
readFields(DataInput) - Method in class org.apache.mahout.classifier.sgd.CrossFoldLearner
 
readFields(DataInput) - Method in class org.apache.mahout.classifier.sgd.ElasticBandPrior
 
readFields(DataInput) - Method in class org.apache.mahout.classifier.sgd.GradientMachine
 
readFields(DataInput) - Method in class org.apache.mahout.classifier.sgd.L1
 
readFields(DataInput) - Method in class org.apache.mahout.classifier.sgd.L2
 
readFields(DataInput) - Method in class org.apache.mahout.classifier.sgd.OnlineLogisticRegression
 
readFields(DataInput) - Method in class org.apache.mahout.classifier.sgd.PassiveAggressive
 
readFields(DataInput) - Method in class org.apache.mahout.classifier.sgd.TPrior
 
readFields(DataInput) - Method in class org.apache.mahout.classifier.sgd.UniformPrior
 
readFields(DataInput) - Method in class org.apache.mahout.clustering.AbstractCluster
 
readFields(DataInput) - Method in class org.apache.mahout.clustering.ClusterClassifier
 
readFields(DataInput) - Method in class org.apache.mahout.clustering.ClusterObservations
 
readFields(DataInput) - Method in class org.apache.mahout.clustering.dirichlet.DirichletCluster
 
readFields(DataInput) - Method in class org.apache.mahout.clustering.DistanceMeasureCluster
 
readFields(DataInput) - Method in class org.apache.mahout.clustering.kmeans.Cluster
 
readFields(DataInput) - Method in class org.apache.mahout.clustering.meanshift.MeanShiftCanopy
 
readFields(DataInput) - Method in class org.apache.mahout.clustering.spectral.common.IntDoublePairWritable
 
readFields(DataInput) - Method in class org.apache.mahout.clustering.spectral.common.VertexWritable
 
readFields(DataInput) - Method in class org.apache.mahout.clustering.spectral.eigencuts.EigencutsSensitivityNode
 
readFields(DataInput) - Method in class org.apache.mahout.clustering.WeightedPropertyVectorWritable
 
readFields(DataInput) - Method in class org.apache.mahout.clustering.WeightedVectorWritable
 
readFields(DataInput) - Method in class org.apache.mahout.common.IntegerTuple
 
readFields(DataInput) - Method in class org.apache.mahout.common.IntPairWritable
 
readFields(DataInput) - Method in class org.apache.mahout.common.IntTuple
 
readFields(DataInput) - Method in class org.apache.mahout.common.StringTuple
 
readFields(DataInput) - Method in class org.apache.mahout.ep.EvolutionaryProcess
 
readFields(DataInput) - Method in class org.apache.mahout.ep.Mapping.Exponential
 
readFields(DataInput) - Method in class org.apache.mahout.ep.Mapping.Identity
 
readFields(DataInput) - Method in class org.apache.mahout.ep.Mapping.LogLimit
 
readFields(DataInput) - Method in class org.apache.mahout.ep.Mapping.SoftLimit
 
readFields(DataInput) - Method in class org.apache.mahout.ep.State
 
readFields(DataInput) - Method in class org.apache.mahout.fpm.pfpgrowth.convertors.string.TopKStringPatterns
 
readFields(DataInput) - Method in class org.apache.mahout.fpm.pfpgrowth.TransactionTree
 
readFields(DataInput) - Method in class org.apache.mahout.math.hadoop.DistributedRowMatrix.MatrixEntryWritable
 
readFields(DataInput) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.DenseBlockWritable
 
readFields(DataInput) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.SparseRowBlockWritable
 
readFields(DataInput) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.SplitPartitionedWritable
 
readFields(DataInput) - Method in class org.apache.mahout.math.MatrixWritable
 
readFields(DataInput) - Method in class org.apache.mahout.math.MultiLabelVectorWritable
 
readFields(DataInput) - Method in class org.apache.mahout.math.stats.GlobalOnlineAuc
 
readFields(DataInput) - Method in class org.apache.mahout.math.stats.GroupedOnlineAuc
 
readFields(DataInput) - Method in class org.apache.mahout.math.VarIntWritable
 
readFields(DataInput) - Method in class org.apache.mahout.math.VarLongWritable
 
readFields(DataInput) - Method in class org.apache.mahout.math.VectorWritable
 
readFields(DataInput) - Method in class org.apache.mahout.vectorizer.collocations.llr.Gram
 
readFields(DataInput) - Method in class org.apache.mahout.vectorizer.collocations.llr.GramKey
 
readFList(Configuration) - Static method in class org.apache.mahout.fpm.pfpgrowth.PFPGrowth
Generates the fList from the serialized string representation
readFList(Parameters) - Static method in class org.apache.mahout.fpm.pfpgrowth.PFPGrowth
read the feature frequency List which is built at the end of the Parallel counting job
readFrequentPattern(Configuration, Path) - Static method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.FPGrowth
 
readFrequentPattern(Configuration, Path) - Static method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth2.FPGrowthIds
 
readFrequentPattern(Configuration, Path) - Static method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth2.FPGrowthObj
 
readFrequentPattern(Parameters) - Static method in class org.apache.mahout.fpm.pfpgrowth.PFPGrowth
Read the Frequent Patterns generated from Text
readIndexFromCache(Configuration) - Static method in class org.apache.mahout.classifier.naivebayes.BayesUtils
 
readInt(Path, Configuration) - Static method in class org.apache.mahout.common.HadoopUtil
 
readIntArray(DataInput) - Static method in class org.apache.mahout.classifier.df.DFUtils
Reads an int[] from a DataInput
readItemIDFromString(String) - Method in class org.apache.mahout.cf.taste.impl.model.file.FileDataModel
Subclasses may wish to override this if ID values in the file are not numeric.
readItemIDIndexMap(String, Configuration) - Static method in class org.apache.mahout.cf.taste.hadoop.TasteHadoopUtils
Reads a binary mapping file
readLabelDocumentCounts(Path, Configuration) - Static method in class org.apache.mahout.classifier.bayes.SequenceFileModelReader
 
readLabelIndex(Configuration, Path) - Static method in class org.apache.mahout.classifier.naivebayes.BayesUtils
 
readLabels(DataInput, Map<String, Integer>, Map<String, Integer>) - Static method in class org.apache.mahout.math.MatrixWritable
 
readLabelSums(Path, Configuration) - Static method in class org.apache.mahout.classifier.bayes.SequenceFileModelReader
 
readMatrix(DataInput) - Static method in class org.apache.mahout.math.MatrixWritable
Reads a typed Matrix instance from the input stream
readModel(DataInput) - Static method in class org.apache.mahout.clustering.dirichlet.DirichletCluster
Reads a typed Model instance from the input stream
readModelFromDir(Path, Configuration) - Static method in class org.apache.mahout.classifier.naivebayes.BayesUtils
 
readNodeArray(DataInput) - Static method in class org.apache.mahout.classifier.df.DFUtils
Reads a Node[] from a DataInput
readPerplexity(Configuration, Path, int) - Static method in class org.apache.mahout.clustering.lda.cvb.CVB0Driver
 
readPrototypeSize(Path) - Static method in class org.apache.mahout.clustering.dirichlet.DirichletDriver
Read the first input vector to determine the prototype size for the modelPrototype
readResult(Path, Configuration, Parameters) - Static method in class org.apache.mahout.classifier.bayes.mapreduce.bayes.BayesClassifierDriver
 
readScoresFromCache(Configuration) - Static method in class org.apache.mahout.classifier.naivebayes.BayesUtils
 
readSigmaJSigmaK(Path, Configuration) - Static method in class org.apache.mahout.classifier.bayes.SequenceFileModelReader
 
readSignedVarInt(DataInput) - Static method in class org.apache.mahout.math.Varint
 
readSignedVarLong(DataInput) - Static method in class org.apache.mahout.math.Varint
 
readTimestampFromString(String) - Method in class org.apache.mahout.cf.taste.impl.model.file.FileDataModel
Subclasses may wish to override this to change how time values in the input file are parsed.
readUnsignedVarInt(DataInput) - Static method in class org.apache.mahout.math.Varint
 
readUnsignedVarLong(DataInput) - Static method in class org.apache.mahout.math.Varint
 
readUserIDFromString(String) - Method in class org.apache.mahout.cf.taste.impl.model.file.FileDataModel
Subclasses may wish to override this if ID values in the file are not numeric.
readVector(DataInput) - Static method in class org.apache.mahout.math.VectorWritable
 
readVocabCount(Path, Configuration) - Static method in class org.apache.mahout.classifier.bayes.SequenceFileModelReader
 
recommend(long, int) - Method in class org.apache.mahout.cf.taste.impl.recommender.AbstractRecommender
Default implementation which just calls Recommender.recommend(long, int, org.apache.mahout.cf.taste.recommender.IDRescorer), with a Rescorer that does nothing.
recommend(long, int) - Method in class org.apache.mahout.cf.taste.impl.recommender.CachingRecommender
 
recommend(long, int, IDRescorer) - Method in class org.apache.mahout.cf.taste.impl.recommender.CachingRecommender
 
recommend(long, int, IDRescorer) - Method in class org.apache.mahout.cf.taste.impl.recommender.GenericItemBasedRecommender
 
recommend(long, int, IDRescorer) - Method in class org.apache.mahout.cf.taste.impl.recommender.GenericUserBasedRecommender
 
recommend(long, int, IDRescorer) - Method in class org.apache.mahout.cf.taste.impl.recommender.ItemAverageRecommender
 
recommend(long, int, IDRescorer) - Method in class org.apache.mahout.cf.taste.impl.recommender.ItemUserAverageRecommender
 
recommend(long, int, IDRescorer) - Method in class org.apache.mahout.cf.taste.impl.recommender.RandomRecommender
 
recommend(long, int, IDRescorer) - Method in class org.apache.mahout.cf.taste.impl.recommender.slopeone.SlopeOneRecommender
 
recommend(long, int, IDRescorer) - Method in class org.apache.mahout.cf.taste.impl.recommender.svd.SVDRecommender
 
recommend(long, int, IDRescorer) - Method in class org.apache.mahout.cf.taste.impl.recommender.TreeClusteringRecommender
 
recommend(long, int, IDRescorer) - Method in class org.apache.mahout.cf.taste.impl.recommender.TreeClusteringRecommender2
 
recommend(long, int) - Method in interface org.apache.mahout.cf.taste.recommender.Recommender
 
recommend(long, int, IDRescorer) - Method in interface org.apache.mahout.cf.taste.recommender.Recommender
 
recommendedBecause(long, long, int) - Method in class org.apache.mahout.cf.taste.impl.recommender.GenericItemBasedRecommender
 
recommendedBecause(long, long, int) - Method in interface org.apache.mahout.cf.taste.recommender.ItemBasedRecommender
Lists the items that were most influential in recommending a given item to a given user.
RecommendedItem - Interface in org.apache.mahout.cf.taste.recommender
Implementations encapsulate items that are recommended, and include the item recommended and a value expressing the strength of the preference.
RecommendedItemsWritable - Class in org.apache.mahout.cf.taste.hadoop
A Writable which encapsulates a list of RecommendedItems.
RecommendedItemsWritable() - Constructor for class org.apache.mahout.cf.taste.hadoop.RecommendedItemsWritable
 
RecommendedItemsWritable(List<RecommendedItem>) - Constructor for class org.apache.mahout.cf.taste.hadoop.RecommendedItemsWritable
 
Recommender - Interface in org.apache.mahout.cf.taste.recommender
Implementations of this interface can recommend items for a user.
RecommenderBuilder - Interface in org.apache.mahout.cf.taste.eval
Implementations of this inner interface are simple helper classes which create a Recommender to be evaluated based on the given DataModel.
RecommenderEvaluator - Interface in org.apache.mahout.cf.taste.eval
Implementations of this interface evaluate the quality of a Recommender's recommendations.
RecommenderIRStatsEvaluator - Interface in org.apache.mahout.cf.taste.eval
Implementations collect information retrieval-related statistics on a Recommender's performance, including precision, recall and f-measure.
RecommenderJob - Class in org.apache.mahout.cf.taste.hadoop.als
Computes the top-N recommendations per user from a decomposition of the rating matrix
RecommenderJob() - Constructor for class org.apache.mahout.cf.taste.hadoop.als.RecommenderJob
 
RecommenderJob - Class in org.apache.mahout.cf.taste.hadoop.item
Runs a completely distributed recommender job as a series of mapreduces.
RecommenderJob() - Constructor for class org.apache.mahout.cf.taste.hadoop.item.RecommenderJob
 
RecommenderJob - Class in org.apache.mahout.cf.taste.hadoop.pseudo
This job runs a "pseudo-distributed" recommendation process on Hadoop.
RecommenderJob() - Constructor for class org.apache.mahout.cf.taste.hadoop.pseudo.RecommenderJob
 
RecommenderReducer - Class in org.apache.mahout.cf.taste.hadoop.pseudo
The Reducer which takes as input the user IDs parsed out by the map phase, and for each unique user ID, computes recommendations with the configured Recommender.
RecommenderReducer() - Constructor for class org.apache.mahout.cf.taste.hadoop.pseudo.RecommenderReducer
 
RecordFactory - Interface in org.apache.mahout.classifier.sgd
A record factor understands how to convert a line of data into fields and then into a vector.
reduce(VarLongWritable, Iterable<PrefAndSimilarityColumnWritable>, Reducer<VarLongWritable, PrefAndSimilarityColumnWritable, VarLongWritable, RecommendedItemsWritable>.Context) - Method in class org.apache.mahout.cf.taste.hadoop.item.AggregateAndRecommendReducer
 
reduce(VarLongWritable, Iterable<VarLongWritable>, Reducer<VarLongWritable, VarLongWritable, VarIntWritable, VectorAndPrefsWritable>.Context) - Method in class org.apache.mahout.cf.taste.hadoop.item.ItemFilterAsVectorAndPrefsReducer
 
reduce(VarIntWritable, Iterable<VarLongWritable>, Reducer<VarIntWritable, VarLongWritable, VarIntWritable, VarLongWritable>.Context) - Method in class org.apache.mahout.cf.taste.hadoop.item.ItemIDIndexReducer
 
reduce(VarLongWritable, Iterable<VarLongWritable>, Reducer<VarLongWritable, VarLongWritable, VarLongWritable, VectorWritable>.Context) - Method in class org.apache.mahout.cf.taste.hadoop.item.ToUserVectorsReducer
 
reduce(VarIntWritable, Iterable<VectorOrPrefWritable>, Reducer<VarIntWritable, VectorOrPrefWritable, VarIntWritable, VectorAndPrefsWritable>.Context) - Method in class org.apache.mahout.cf.taste.hadoop.item.ToVectorAndPrefReducer
 
reduce(IntWritable, Iterable<VectorWritable>, Reducer<IntWritable, VectorWritable, IntWritable, VectorWritable>.Context) - Method in class org.apache.mahout.cf.taste.hadoop.preparation.ToItemVectorsReducer
 
reduce(VarLongWritable, Iterable<NullWritable>, Reducer<VarLongWritable, NullWritable, VarLongWritable, RecommendedItemsWritable>.Context) - Method in class org.apache.mahout.cf.taste.hadoop.pseudo.RecommenderReducer
 
reduce(EntityEntityWritable, Iterable<FloatWritable>, Reducer<EntityEntityWritable, FloatWritable, EntityEntityWritable, FullRunningAverageAndStdDevWritable>.Context) - Method in class org.apache.mahout.cf.taste.hadoop.slopeone.SlopeOneDiffsToAveragesReducer
 
reduce(VarLongWritable, Iterable<EntityPrefWritable>, Reducer<VarLongWritable, EntityPrefWritable, EntityEntityWritable, FloatWritable>.Context) - Method in class org.apache.mahout.cf.taste.hadoop.slopeone.SlopeOnePrefsToDiffsReducer
 
reduce(StringTuple, Iterator<DoubleWritable>, OutputCollector<StringTuple, DoubleWritable>, Reporter) - Method in class org.apache.mahout.classifier.bayes.mapreduce.bayes.BayesClassifierReducer
 
reduce(StringTuple, Iterator<DoubleWritable>, OutputCollector<StringTuple, DoubleWritable>, Reporter) - Method in class org.apache.mahout.classifier.bayes.mapreduce.bayes.BayesThetaNormalizerReducer
 
reduce(StringTuple, Iterator<DoubleWritable>, OutputCollector<StringTuple, DoubleWritable>, Reporter) - Method in class org.apache.mahout.classifier.bayes.mapreduce.cbayes.CBayesThetaNormalizerReducer
 
reduce(StringTuple, Iterator<DoubleWritable>, OutputCollector<StringTuple, DoubleWritable>, Reporter) - Method in class org.apache.mahout.classifier.bayes.mapreduce.common.BayesFeatureCombiner
 
reduce(StringTuple, Iterator<DoubleWritable>, OutputCollector<StringTuple, DoubleWritable>, Reporter) - Method in class org.apache.mahout.classifier.bayes.mapreduce.common.BayesFeatureReducer
 
reduce(StringTuple, Iterator<DoubleWritable>, OutputCollector<StringTuple, DoubleWritable>, Reporter) - Method in class org.apache.mahout.classifier.bayes.mapreduce.common.BayesTfIdfReducer
 
reduce(StringTuple, Iterator<DoubleWritable>, OutputCollector<StringTuple, DoubleWritable>, Reporter) - Method in class org.apache.mahout.classifier.bayes.mapreduce.common.BayesWeightSummerReducer
 
reduce(Text, Iterable<VectorWritable>, Reducer<Text, VectorWritable, Text, Canopy>.Context) - Method in class org.apache.mahout.clustering.canopy.CanopyReducer
 
reduce(IntWritable, Iterable<Cluster>, Reducer<IntWritable, Cluster, IntWritable, Cluster>.Context) - Method in class org.apache.mahout.clustering.CIReducer
 
reduce(Text, Iterable<VectorWritable>, Reducer<Text, VectorWritable, Text, DirichletCluster>.Context) - Method in class org.apache.mahout.clustering.dirichlet.DirichletReducer
 
reduce(Text, Iterable<ClusterObservations>, Reducer<Text, ClusterObservations, Text, ClusterObservations>.Context) - Method in class org.apache.mahout.clustering.fuzzykmeans.FuzzyKMeansCombiner
 
reduce(Text, Iterable<ClusterObservations>, Reducer<Text, ClusterObservations, Text, SoftCluster>.Context) - Method in class org.apache.mahout.clustering.fuzzykmeans.FuzzyKMeansReducer
 
reduce(Text, Iterable<ClusterObservations>, Reducer<Text, ClusterObservations, Text, ClusterObservations>.Context) - Method in class org.apache.mahout.clustering.kmeans.KMeansCombiner
 
reduce(Text, Iterable<ClusterObservations>, Reducer<Text, ClusterObservations, Text, Cluster>.Context) - Method in class org.apache.mahout.clustering.kmeans.KMeansReducer
 
reduce(IntPairWritable, Iterable<DoubleWritable>, Reducer<IntPairWritable, DoubleWritable, IntPairWritable, DoubleWritable>.Context) - Method in class org.apache.mahout.clustering.lda.LDAReducer
 
reduce(Text, Iterable<MeanShiftCanopy>, Reducer<Text, MeanShiftCanopy, Text, MeanShiftCanopy>.Context) - Method in class org.apache.mahout.clustering.meanshift.MeanShiftCanopyReducer
 
reduce(Text, Iterable<Writable>, Reducer<Text, Writable, Text, Writable>.Context) - Method in class org.apache.mahout.clustering.minhash.MinHashReducer
output the items clustered
reduce(IntWritable, Iterable<DistributedRowMatrix.MatrixEntryWritable>, Reducer<IntWritable, DistributedRowMatrix.MatrixEntryWritable, IntWritable, VectorWritable>.Context) - Method in class org.apache.mahout.clustering.spectral.common.AffinityMatrixInputReducer
 
reduce(NullWritable, Iterable<IntDoublePairWritable>, Reducer<NullWritable, IntDoublePairWritable, NullWritable, VectorWritable>.Context) - Method in class org.apache.mahout.clustering.spectral.common.MatrixDiagonalizeJob.MatrixDiagonalizeReducer
 
reduce(Text, Iterable<VertexWritable>, Reducer<Text, VertexWritable, Text, VertexWritable>.Context) - Method in class org.apache.mahout.clustering.spectral.eigencuts.EigencutsAffinityCutsJob.EigencutsAffinityCutsCombiner
 
reduce(Text, Iterable<VertexWritable>, Reducer<Text, VertexWritable, IntWritable, VectorWritable>.Context) - Method in class org.apache.mahout.clustering.spectral.eigencuts.EigencutsAffinityCutsJob.EigencutsAffinityCutsReducer
 
reduce(IntWritable, Iterable<EigencutsSensitivityNode>, Reducer<IntWritable, EigencutsSensitivityNode, IntWritable, VectorWritable>.Context) - Method in class org.apache.mahout.clustering.spectral.eigencuts.EigencutsSensitivityReducer
 
reduce(Text, Iterable<VectorWritable>, Reducer<Text, VectorWritable, Text, VectorWritable>.Context) - Method in class org.apache.mahout.clustering.topdown.postprocessor.ClusterOutputPostProcessorReducer
The key is the cluster id and the values contains the points in that cluster.
reduce(WritableComparable<?>, Iterable<VectorWritable>, Reducer<WritableComparable<?>, VectorWritable, WritableComparable<?>, VectorWritable>.Context) - Method in class org.apache.mahout.common.mapreduce.MergeVectorsCombiner
 
reduce(WritableComparable<?>, Iterable<VectorWritable>, Reducer<WritableComparable<?>, VectorWritable, WritableComparable<?>, VectorWritable>.Context) - Method in class org.apache.mahout.common.mapreduce.MergeVectorsReducer
 
reduce(WritableComparable<?>, Iterable<VectorWritable>, Reducer<WritableComparable<?>, VectorWritable, WritableComparable<?>, VectorWritable>.Context) - Method in class org.apache.mahout.common.mapreduce.VectorSumReducer
 
reduce(Text, Iterable<TopKStringPatterns>, Reducer<Text, TopKStringPatterns, Text, TopKStringPatterns>.Context) - Method in class org.apache.mahout.fpm.pfpgrowth.AggregatorReducer
 
reduce(Text, Iterable<LongWritable>, Reducer<Text, LongWritable, Text, LongWritable>.Context) - Method in class org.apache.mahout.fpm.pfpgrowth.ParallelCountingReducer
 
reduce(IntWritable, Iterable<TransactionTree>, Reducer<IntWritable, TransactionTree, IntWritable, TransactionTree>.Context) - Method in class org.apache.mahout.fpm.pfpgrowth.ParallelFPGrowthCombiner
 
reduce(IntWritable, Iterable<TransactionTree>, Reducer<IntWritable, TransactionTree, Text, TopKStringPatterns>.Context) - Method in class org.apache.mahout.fpm.pfpgrowth.ParallelFPGrowthReducer
 
reduce(IntWritable, Iterator<VectorWritable>, OutputCollector<IntWritable, VectorWritable>, Reporter) - Method in class org.apache.mahout.math.hadoop.MatrixMultiplicationJob.MatrixMultiplicationReducer
 
reduce(IntWritable, Iterable<VectorWritable>, Reducer<IntWritable, VectorWritable, IntWritable, VectorWritable>.Context) - Method in class org.apache.mahout.math.hadoop.similarity.cooccurrence.RowSimilarityJob.MergeToTopKSimilaritiesReducer
 
reduce(IntWritable, Iterable<VectorWritable>, Reducer<IntWritable, VectorWritable, IntWritable, VectorWritable>.Context) - Method in class org.apache.mahout.math.hadoop.similarity.cooccurrence.RowSimilarityJob.MergeVectorsCombiner
 
reduce(IntWritable, Iterable<VectorWritable>, Reducer<IntWritable, VectorWritable, IntWritable, VectorWritable>.Context) - Method in class org.apache.mahout.math.hadoop.similarity.cooccurrence.RowSimilarityJob.MergeVectorsReducer
 
reduce(IntWritable, Iterable<VectorWritable>, Reducer<IntWritable, VectorWritable, IntWritable, VectorWritable>.Context) - Method in class org.apache.mahout.math.hadoop.similarity.cooccurrence.RowSimilarityJob.SimilarityReducer
 
reduce(IntWritable, Iterable<DoubleWritable>, Reducer<IntWritable, DoubleWritable, IntWritable, DoubleWritable>.Context) - Method in class org.apache.mahout.math.hadoop.stats.StandardDeviationCalculatorReducer
 
reduce(SplitPartitionedWritable, Iterable<DenseBlockWritable>, Reducer<SplitPartitionedWritable, DenseBlockWritable, SplitPartitionedWritable, VectorWritable>.Context) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.ABtDenseOutJob.QRReducer
 
reduce(SplitPartitionedWritable, Iterable<SparseRowBlockWritable>, Reducer<SplitPartitionedWritable, SparseRowBlockWritable, SplitPartitionedWritable, VectorWritable>.Context) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.ABtJob.QRReducer
 
reduce(Writable, Iterable<SparseRowBlockWritable>, Reducer<Writable, SparseRowBlockWritable, Writable, SparseRowBlockWritable>.Context) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.BtJob.OuterProductCombiner
 
reduce(LongWritable, Iterable<SparseRowBlockWritable>, Reducer<LongWritable, SparseRowBlockWritable, IntWritable, VectorWritable>.Context) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.BtJob.OuterProductReducer
 
reduce(IntWritable, Iterable<VectorWritable>, Reducer<IntWritable, VectorWritable, IntWritable, VectorWritable>.Context) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.YtYJob.YtYReducer
 
reduce(NullWritable, Iterator<VectorWritable>, OutputCollector<NullWritable, VectorWritable>, Reporter) - Method in class org.apache.mahout.math.hadoop.TimesSquaredJob.VectorSummingReducer
 
reduce(WritableComparable<?>, Iterator<VectorWritable>, OutputCollector<WritableComparable<?>, VectorWritable>, Reporter) - Method in class org.apache.mahout.math.hadoop.TransposeJob.MergeVectorsCombiner
 
reduce(WritableComparable<?>, Iterator<VectorWritable>, OutputCollector<WritableComparable<?>, VectorWritable>, Reporter) - Method in class org.apache.mahout.math.hadoop.TransposeJob.MergeVectorsReducer
 
reduce(NullWritable, Iterable<DoubleWritable>, Reducer<NullWritable, DoubleWritable, NullWritable, DoubleWritable>.Context) - Method in class org.apache.mahout.math.stats.entropy.CalculateEntropyReducer
 
reduce(Writable, Iterable<DoubleWritable>, Reducer<Writable, DoubleWritable, Writable, DoubleWritable>.Context) - Method in class org.apache.mahout.math.stats.entropy.DoubleSumReducer
 
reduce(Text, Iterable<VarIntWritable>, Reducer<Text, VarIntWritable, Text, DoubleWritable>.Context) - Method in class org.apache.mahout.math.stats.entropy.SpecificConditionalEntropyReducer
 
reduce(Writable, Iterable<VarIntWritable>, Reducer<Writable, VarIntWritable, Writable, VarIntWritable>.Context) - Method in class org.apache.mahout.math.stats.entropy.VarIntSumReducer
 
reduce(GramKey, Iterable<Gram>, Reducer<GramKey, Gram, GramKey, Gram>.Context) - Method in class org.apache.mahout.vectorizer.collocations.llr.CollocCombiner
 
reduce(GramKey, Iterable<Gram>, Reducer<GramKey, Gram, Gram, Gram>.Context) - Method in class org.apache.mahout.vectorizer.collocations.llr.CollocReducer
collocation finder: pass 1 reduce phase:

given input from the mapper,

reduce(Gram, Iterable<Gram>, Reducer<Gram, Gram, Text, DoubleWritable>.Context) - Method in class org.apache.mahout.vectorizer.collocations.llr.LLRReducer
Perform LLR calculation, input is: k:ngram:ngramFreq v:(h_|t_)subgram:subgramfreq N = ngram total Each ngram will have 2 subgrams, a head and a tail, referred to as A and B respectively below.
reduce(WritableComparable<?>, Iterable<VectorWritable>, Reducer<WritableComparable<?>, VectorWritable, WritableComparable<?>, VectorWritable>.Context) - Method in class org.apache.mahout.vectorizer.common.PartialVectorMergeReducer
 
reduce(WritableComparable<?>, Iterable<VectorWritable>, Reducer<WritableComparable<?>, VectorWritable, WritableComparable<?>, VectorWritable>.Context) - Method in class org.apache.mahout.vectorizer.pruner.PrunedPartialVectorMergeReducer
 
reduce(WritableComparable<?>, Iterable<VectorWritable>, Reducer<WritableComparable<?>, VectorWritable, WritableComparable<?>, VectorWritable>.Context) - Method in class org.apache.mahout.vectorizer.pruner.WordsPrunerReducer
 
reduce(Text, Iterable<LongWritable>, Reducer<Text, LongWritable, Text, LongWritable>.Context) - Method in class org.apache.mahout.vectorizer.term.TermCountCombiner
 
reduce(Text, Iterable<LongWritable>, Reducer<Text, LongWritable, Text, LongWritable>.Context) - Method in class org.apache.mahout.vectorizer.term.TermCountReducer
 
reduce(IntWritable, Iterable<LongWritable>, Reducer<IntWritable, LongWritable, IntWritable, LongWritable>.Context) - Method in class org.apache.mahout.vectorizer.term.TermDocumentCountReducer
 
reduce(Text, Iterable<StringTuple>, Reducer<Text, StringTuple, Text, VectorWritable>.Context) - Method in class org.apache.mahout.vectorizer.term.TFPartialVectorReducer
 
reduce(WritableComparable<?>, Iterable<VectorWritable>, Reducer<WritableComparable<?>, VectorWritable, WritableComparable<?>, VectorWritable>.Context) - Method in class org.apache.mahout.vectorizer.tfidf.TFIDFPartialVectorReducer
 
ReducerMetrics - Enum in org.apache.mahout.cf.taste.hadoop.pseudo
Custom metrics collected by RecommenderReducer.
refresh(Collection<Refreshable>) - Method in interface org.apache.mahout.cf.taste.common.Refreshable
Triggers "refresh" -- whatever that means -- of the implementation.
refresh(Collection<Refreshable>) - Method in class org.apache.mahout.cf.taste.impl.common.RefreshHelper
Typically this is called in and is the entire body of that method.
refresh(Collection<Refreshable>) - Method in class org.apache.mahout.cf.taste.impl.model.AbstractIDMigrator
 
refresh(Collection<Refreshable>) - Method in class org.apache.mahout.cf.taste.impl.model.file.FileDataModel
 
refresh(Collection<Refreshable>) - Method in class org.apache.mahout.cf.taste.impl.model.file.FileIDMigrator
 
refresh(Collection<Refreshable>) - Method in class org.apache.mahout.cf.taste.impl.model.GenericBooleanPrefDataModel
 
refresh(Collection<Refreshable>) - Method in class org.apache.mahout.cf.taste.impl.model.GenericDataModel
 
refresh(Collection<Refreshable>) - Method in class org.apache.mahout.cf.taste.impl.model.PlusAnonymousUserDataModel
 
refresh(Collection<Refreshable>) - Method in class org.apache.mahout.cf.taste.impl.neighborhood.CachingUserNeighborhood
 
refresh(Collection<Refreshable>) - Method in class org.apache.mahout.cf.taste.impl.recommender.CachingRecommender
 
refresh(Collection<Refreshable>) - Method in class org.apache.mahout.cf.taste.impl.recommender.FarthestNeighborClusterSimilarity
 
refresh(Collection<Refreshable>) - Method in class org.apache.mahout.cf.taste.impl.recommender.GenericItemBasedRecommender
 
refresh(Collection<Refreshable>) - Method in class org.apache.mahout.cf.taste.impl.recommender.GenericUserBasedRecommender
 
refresh(Collection<Refreshable>) - Method in class org.apache.mahout.cf.taste.impl.recommender.ItemAverageRecommender
 
refresh(Collection<Refreshable>) - Method in class org.apache.mahout.cf.taste.impl.recommender.ItemUserAverageRecommender
 
refresh(Collection<Refreshable>) - Method in class org.apache.mahout.cf.taste.impl.recommender.NearestNeighborClusterSimilarity
 
refresh(Collection<Refreshable>) - Method in class org.apache.mahout.cf.taste.impl.recommender.RandomRecommender
 
refresh(Collection<Refreshable>) - Method in class org.apache.mahout.cf.taste.impl.recommender.slopeone.file.FileDiffStorage
 
refresh(Collection<Refreshable>) - Method in class org.apache.mahout.cf.taste.impl.recommender.slopeone.MemoryDiffStorage
 
refresh(Collection<Refreshable>) - Method in class org.apache.mahout.cf.taste.impl.recommender.slopeone.SlopeOneRecommender
 
refresh(Collection<Refreshable>) - Method in class org.apache.mahout.cf.taste.impl.recommender.svd.AbstractFactorizer
 
refresh(Collection<Refreshable>) - Method in class org.apache.mahout.cf.taste.impl.recommender.svd.SVDRecommender
Refresh the data model and factorization.
refresh(Collection<Refreshable>) - Method in class org.apache.mahout.cf.taste.impl.recommender.TreeClusteringRecommender
 
refresh(Collection<Refreshable>) - Method in class org.apache.mahout.cf.taste.impl.recommender.TreeClusteringRecommender2
 
refresh(Collection<Refreshable>) - Method in class org.apache.mahout.cf.taste.impl.similarity.AbstractItemSimilarity
 
refresh(Collection<Refreshable>) - Method in class org.apache.mahout.cf.taste.impl.similarity.AveragingPreferenceInferrer
 
refresh(Collection<Refreshable>) - Method in class org.apache.mahout.cf.taste.impl.similarity.CachingItemSimilarity
 
refresh(Collection<Refreshable>) - Method in class org.apache.mahout.cf.taste.impl.similarity.CachingUserSimilarity
 
refresh(Collection<Refreshable>) - Method in class org.apache.mahout.cf.taste.impl.similarity.CityBlockSimilarity
 
refresh(Collection<Refreshable>) - Method in class org.apache.mahout.cf.taste.impl.similarity.file.FileItemSimilarity
 
refresh(Collection<Refreshable>) - Method in class org.apache.mahout.cf.taste.impl.similarity.GenericItemSimilarity
 
refresh(Collection<Refreshable>) - Method in class org.apache.mahout.cf.taste.impl.similarity.GenericUserSimilarity
 
refresh(Collection<Refreshable>) - Method in class org.apache.mahout.cf.taste.impl.similarity.LogLikelihoodSimilarity
 
refresh(Collection<Refreshable>) - Method in class org.apache.mahout.cf.taste.impl.similarity.SpearmanCorrelationSimilarity
 
refresh(Collection<Refreshable>) - Method in class org.apache.mahout.cf.taste.impl.similarity.TanimotoCoefficientSimilarity
 
refresh(Collection<Refreshable>) - Method in class org.apache.mahout.cf.taste.impl.transforms.CaseAmplification
 
refresh(Collection<Refreshable>) - Method in class org.apache.mahout.cf.taste.impl.transforms.InverseUserFrequency
 
refresh(Collection<Refreshable>) - Method in class org.apache.mahout.cf.taste.impl.transforms.ZScore
 
Refreshable - Interface in org.apache.mahout.cf.taste.common
Implementations of this interface have state that can be periodically refreshed.
RefreshHelper - Class in org.apache.mahout.cf.taste.impl.common
A helper class for implementing Refreshable.
RefreshHelper(Callable<?>) - Constructor for class org.apache.mahout.cf.taste.impl.common.RefreshHelper
 
registerHiddenStateNames(String[]) - Method in class org.apache.mahout.classifier.sequencelearning.hmm.HmmModel
Register an array of hidden state Names.
registerHiddenStateNames(Map<String, Integer>) - Method in class org.apache.mahout.classifier.sequencelearning.hmm.HmmModel
Register a map of hidden state Names/state IDs
registerOutputStateNames(String[]) - Method in class org.apache.mahout.classifier.sequencelearning.hmm.HmmModel
Register an array of hidden state Names.
registerOutputStateNames(Map<String, Integer>) - Method in class org.apache.mahout.classifier.sequencelearning.hmm.HmmModel
Register a map of hidden state Names/state IDs
RegressionResultAnalyzer - Class in org.apache.mahout.classifier
ResultAnalyzer captures the classification statistics and displays in a tabular manner
RegressionResultAnalyzer() - Constructor for class org.apache.mahout.classifier.RegressionResultAnalyzer
 
RegressionSplit - Class in org.apache.mahout.classifier.df.split
Regression problem implementation of IgSplit.
RegressionSplit() - Constructor for class org.apache.mahout.classifier.df.split.RegressionSplit
 
regularization(double) - Method in class org.apache.mahout.classifier.sgd.GradientMachine
Chainable configuration option.
regularize(Vector) - Method in class org.apache.mahout.classifier.sgd.AbstractOnlineLogisticRegression
 
rehash() - Method in class org.apache.mahout.cf.taste.impl.common.FastByIDMap
 
rehash() - Method in class org.apache.mahout.cf.taste.impl.common.FastIDSet
 
rehash() - Method in class org.apache.mahout.cf.taste.impl.common.FastMap
 
RelevantItemsDataSplitter - Interface in org.apache.mahout.cf.taste.eval
Implementations of this interface determine the items that are considered relevant, and splits data into a training and test subset, for purposes of precision/recall tests as implemented by implementations of RecommenderIRStatsEvaluator.
reload() - Method in class org.apache.mahout.cf.taste.impl.model.file.FileDataModel
 
reload() - Method in class org.apache.mahout.cf.taste.impl.similarity.file.FileItemSimilarity
 
remove(K) - Method in class org.apache.mahout.cf.taste.impl.common.Cache
Uncaches any existing value for a given key.
remove(long) - Method in class org.apache.mahout.cf.taste.impl.common.FastByIDMap
 
remove(long) - Method in class org.apache.mahout.cf.taste.impl.common.FastIDSet
 
remove(Object) - Method in class org.apache.mahout.cf.taste.impl.common.FastMap
 
remove() - Method in class org.apache.mahout.cf.taste.impl.common.LongPrimitiveArrayIterator
 
remove() - Method in class org.apache.mahout.cf.taste.impl.common.SamplingLongPrimitiveIterator
 
remove() - Method in class org.apache.mahout.math.hadoop.stochasticsvd.qr.QRLastStep
 
removeAll(long[]) - Method in class org.apache.mahout.cf.taste.impl.common.FastIDSet
 
removeAll(FastIDSet) - Method in class org.apache.mahout.cf.taste.impl.common.FastIDSet
 
removeDatum(double) - Method in class org.apache.mahout.cf.taste.impl.common.FixedRunningAverage
 
removeDatum(double) - Method in class org.apache.mahout.cf.taste.impl.common.FullRunningAverage
 
removeDatum(double) - Method in class org.apache.mahout.cf.taste.impl.common.FullRunningAverageAndStdDev
 
removeDatum(double) - Method in class org.apache.mahout.cf.taste.impl.common.InvertedRunningAverage
 
removeDatum(double) - Method in class org.apache.mahout.cf.taste.impl.common.InvertedRunningAverageAndStdDev
 
removeDatum(double) - Method in interface org.apache.mahout.cf.taste.impl.common.RunningAverage
 
removeDatum(double) - Method in class org.apache.mahout.cf.taste.impl.common.WeightedRunningAverage
 
removeDatum(double, double) - Method in class org.apache.mahout.cf.taste.impl.common.WeightedRunningAverage
 
removeDatum(double, double) - Method in class org.apache.mahout.cf.taste.impl.common.WeightedRunningAverageAndStdDev
 
removeDependency(Refreshable) - Method in class org.apache.mahout.cf.taste.impl.common.RefreshHelper
 
removeHeaderNext(int) - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.FPTree
 
removeItemPref(long, long, float) - Method in class org.apache.mahout.cf.taste.impl.recommender.slopeone.file.FileDiffStorage
 
removeItemPref(long, long, float) - Method in class org.apache.mahout.cf.taste.impl.recommender.slopeone.MemoryDiffStorage
 
removeItemPref(long, long, float) - Method in interface org.apache.mahout.cf.taste.recommender.slopeone.DiffStorage
Updates internal data structures to reflect an update in a preference value for an item.
removeKeysMatching(Cache.MatchPredicate<K>) - Method in class org.apache.mahout.cf.taste.impl.common.Cache
Clears all cache entries whose key matches the given predicate.
removePreference(long, long) - Method in class org.apache.mahout.cf.taste.impl.model.file.FileDataModel
See the warning at FileDataModel.setPreference(long, long, float).
removePreference(long, long) - Method in class org.apache.mahout.cf.taste.impl.model.GenericBooleanPrefDataModel
 
removePreference(long, long) - Method in class org.apache.mahout.cf.taste.impl.model.GenericDataModel
 
removePreference(long, long) - Method in class org.apache.mahout.cf.taste.impl.model.PlusAnonymousUserDataModel
 
removePreference(long, long) - Method in class org.apache.mahout.cf.taste.impl.recommender.AbstractRecommender
Default implementation which just calls DataModel.removePreference(long, long) (Object, Object)}.
removePreference(long, long) - Method in class org.apache.mahout.cf.taste.impl.recommender.CachingRecommender
 
removePreference(long, long) - Method in class org.apache.mahout.cf.taste.impl.recommender.ItemAverageRecommender
 
removePreference(long, long) - Method in class org.apache.mahout.cf.taste.impl.recommender.ItemUserAverageRecommender
 
removePreference(long, long) - Method in class org.apache.mahout.cf.taste.impl.recommender.slopeone.SlopeOneRecommender
 
removePreference(long, long) - Method in interface org.apache.mahout.cf.taste.model.DataModel
Removes a particular preference for a user.
removePreference(long, long) - Method in interface org.apache.mahout.cf.taste.recommender.Recommender
 
removeValueMatching(Cache.MatchPredicate<V>) - Method in class org.apache.mahout.cf.taste.impl.common.Cache
Clears all cache entries whose value matches the given predicate.
renormalize() - Method in class org.apache.mahout.clustering.lda.cvb.TopicModel
 
reorderHeaderTable() - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.FPTree
 
replaceAt(int, Integer) - Method in class org.apache.mahout.common.IntegerTuple
Replaces the string at the given index with the given newString
replaceAt(int, int) - Method in class org.apache.mahout.common.IntTuple
Replaces the string at the given index with the given newInteger
replaceAt(int, String) - Method in class org.apache.mahout.common.StringTuple
Replaces the string at the given index with the given newString
replaceChild(int, int, int) - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.FPTree
 
rescore(T, double) - Method in class org.apache.mahout.cf.taste.impl.recommender.NullRescorer
 
rescore(long, double) - Method in class org.apache.mahout.cf.taste.impl.recommender.NullRescorer
 
rescore(long, double) - Method in interface org.apache.mahout.cf.taste.recommender.IDRescorer
 
rescore(T, double) - Method in interface org.apache.mahout.cf.taste.recommender.Rescorer
 
Rescorer<T> - Interface in org.apache.mahout.cf.taste.recommender
A simply assigns a new "score" to a thing like an ID of an item or user which a Recommender is considering returning as a top recommendation.
reset() - Method in class org.apache.mahout.cf.taste.impl.eval.AbstractDifferenceRecommenderEvaluator
 
reset() - Method in class org.apache.mahout.cf.taste.impl.eval.AverageAbsoluteDifferenceRecommenderEvaluator
 
reset() - Method in class org.apache.mahout.cf.taste.impl.eval.RMSRecommenderEvaluator
 
reset() - Method in class org.apache.mahout.clustering.lda.cvb.TopicModel
 
reset() - Method in class org.apache.mahout.math.hadoop.stochasticsvd.qr.GivensThinSolver
 
resetLineCounter() - Method in class org.apache.mahout.classifier.sgd.CrossFoldLearner
 
ResultAnalyzer - Class in org.apache.mahout.classifier
ResultAnalyzer captures the classification statistics and displays in a tabular manner
ResultAnalyzer(Collection<String>, String) - Constructor for class org.apache.mahout.classifier.ResultAnalyzer
 
ResultSetIterator<T> - Class in org.apache.mahout.cf.taste.impl.common.jdbc
 
ResultSetIterator(DataSource, String) - Constructor for class org.apache.mahout.cf.taste.impl.common.jdbc.ResultSetIterator
 
retainAll(FastIDSet) - Method in class org.apache.mahout.cf.taste.impl.common.FastIDSet
 
retrievePerLabelThetaNormalizer() - Method in class org.apache.mahout.classifier.naivebayes.training.AbstractThetaTrainer
 
Retriever<K,V> - Interface in org.apache.mahout.cf.taste.impl.common
Implementations can retrieve a value for a given key.
retrieveTimesSquaredOutputVector(Configuration) - Static method in class org.apache.mahout.math.hadoop.TimesSquaredJob
 
reusableTokenStream(String, Reader) - Method in class org.apache.mahout.vectorizer.DefaultAnalyzer
 
rGamma(double, double) - Static method in class org.apache.mahout.clustering.dirichlet.UncommonDistributions
Returns a double sampled according to this distribution.
rhatCollector - Variable in class org.apache.mahout.math.hadoop.stochasticsvd.ABtDenseOutJob.QRReducer
 
rhatCollector - Variable in class org.apache.mahout.math.hadoop.stochasticsvd.ABtJob.QRReducer
 
RMSRecommenderEvaluator - Class in org.apache.mahout.cf.taste.impl.eval
A RecommenderEvaluator which computes the "root mean squared" difference between predicted and actual ratings for users.
RMSRecommenderEvaluator() - Constructor for class org.apache.mahout.cf.taste.impl.eval.RMSRecommenderEvaluator
 
rMultinom(Vector) - Static method in class org.apache.mahout.clustering.dirichlet.UncommonDistributions
Returns one sample from a multinomial.
rMultinom(int, Vector) - Static method in class org.apache.mahout.clustering.dirichlet.UncommonDistributions
Returns a multinomial vector sampled from the given probabilities rmultinom should be implemented as successive binomial sampling.
rNorm(double, double) - Static method in class org.apache.mahout.clustering.dirichlet.UncommonDistributions
Return a random value from a normal distribution with the given mean and standard deviation
root() - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth2.FPTree
Returns the root node of the tree.
ROOTNODEID - Static variable in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.FPTree
 
RowSimilarityJob - Class in org.apache.mahout.math.hadoop.similarity.cooccurrence
 
RowSimilarityJob() - Constructor for class org.apache.mahout.math.hadoop.similarity.cooccurrence.RowSimilarityJob
 
RowSimilarityJob.CooccurrencesMapper - Class in org.apache.mahout.math.hadoop.similarity.cooccurrence
 
RowSimilarityJob.CooccurrencesMapper() - Constructor for class org.apache.mahout.math.hadoop.similarity.cooccurrence.RowSimilarityJob.CooccurrencesMapper
 
RowSimilarityJob.MergeToTopKSimilaritiesReducer - Class in org.apache.mahout.math.hadoop.similarity.cooccurrence
 
RowSimilarityJob.MergeToTopKSimilaritiesReducer() - Constructor for class org.apache.mahout.math.hadoop.similarity.cooccurrence.RowSimilarityJob.MergeToTopKSimilaritiesReducer
 
RowSimilarityJob.MergeVectorsCombiner - Class in org.apache.mahout.math.hadoop.similarity.cooccurrence
 
RowSimilarityJob.MergeVectorsCombiner() - Constructor for class org.apache.mahout.math.hadoop.similarity.cooccurrence.RowSimilarityJob.MergeVectorsCombiner
 
RowSimilarityJob.MergeVectorsReducer - Class in org.apache.mahout.math.hadoop.similarity.cooccurrence
 
RowSimilarityJob.MergeVectorsReducer() - Constructor for class org.apache.mahout.math.hadoop.similarity.cooccurrence.RowSimilarityJob.MergeVectorsReducer
 
RowSimilarityJob.SimilarityReducer - Class in org.apache.mahout.math.hadoop.similarity.cooccurrence
 
RowSimilarityJob.SimilarityReducer() - Constructor for class org.apache.mahout.math.hadoop.similarity.cooccurrence.RowSimilarityJob.SimilarityReducer
 
RowSimilarityJob.UnsymmetrifyMapper - Class in org.apache.mahout.math.hadoop.similarity.cooccurrence
 
RowSimilarityJob.UnsymmetrifyMapper() - Constructor for class org.apache.mahout.math.hadoop.similarity.cooccurrence.RowSimilarityJob.UnsymmetrifyMapper
 
RowSimilarityJob.VectorNormMapper - Class in org.apache.mahout.math.hadoop.similarity.cooccurrence
 
RowSimilarityJob.VectorNormMapper() - Constructor for class org.apache.mahout.math.hadoop.similarity.cooccurrence.RowSimilarityJob.VectorNormMapper
 
rsplit(Random, int) - Method in class org.apache.mahout.classifier.df.data.Data
Splits the data in two, returns one part, and this gets the rest of the data.
run(String[]) - Method in class org.apache.mahout.cf.taste.hadoop.als.DatasetSplitter
 
run(String[]) - Method in class org.apache.mahout.cf.taste.hadoop.als.FactorizationEvaluator
 
run(String[]) - Method in class org.apache.mahout.cf.taste.hadoop.als.ParallelALSFactorizationJob
 
run(String[]) - Method in class org.apache.mahout.cf.taste.hadoop.als.RecommenderJob
 
run(String[]) - Method in class org.apache.mahout.cf.taste.hadoop.item.RecommenderJob
 
run(String[]) - Method in class org.apache.mahout.cf.taste.hadoop.preparation.PreparePreferenceMatrixJob
 
run(String[]) - Method in class org.apache.mahout.cf.taste.hadoop.pseudo.RecommenderJob
 
run(String[]) - Method in class org.apache.mahout.cf.taste.hadoop.similarity.item.ItemSimilarityJob
 
run(String[]) - Method in class org.apache.mahout.cf.taste.hadoop.slopeone.SlopeOneAverageDiffsJob
 
run() - Method in class org.apache.mahout.classifier.df.mapreduce.Classifier
 
run(String[]) - Method in class org.apache.mahout.classifier.df.tools.Frequencies
 
run(Configuration) - Method in class org.apache.mahout.classifier.df.tools.FrequenciesJob
 
run(String[]) - Method in class org.apache.mahout.classifier.naivebayes.test.TestNaiveBayesDriver
 
run(String[]) - Method in class org.apache.mahout.classifier.naivebayes.training.TrainNaiveBayesJob
 
run(String[]) - Method in class org.apache.mahout.clustering.canopy.CanopyDriver
 
run(Configuration, Path, Path, DistanceMeasure, double, double, double, double, int, boolean, boolean) - Static method in class org.apache.mahout.clustering.canopy.CanopyDriver
Build a directory of Canopy clusters from the input arguments and, if requested, cluster the input vectors using these clusters
run(Configuration, Path, Path, DistanceMeasure, double, double, boolean, boolean) - Static method in class org.apache.mahout.clustering.canopy.CanopyDriver
Convenience method to provide backward compatibility
run(Path, Path, DistanceMeasure, double, double, boolean, boolean) - Static method in class org.apache.mahout.clustering.canopy.CanopyDriver
Convenience method creates new Configuration() Build a directory of Canopy clusters from the input arguments and, if requested, cluster the input vectors using these clusters
run(String[]) - Method in class org.apache.mahout.clustering.dirichlet.DirichletDriver
 
run(Configuration, Path, Path, DistributionDescription, int, int, double, boolean, boolean, double, boolean) - Static method in class org.apache.mahout.clustering.dirichlet.DirichletDriver
Iterate over the input vectors to produce clusters and, if requested, use the results of the final iteration to cluster the input vectors.
run(Path, Path, DistributionDescription, int, int, double, boolean, boolean, double, boolean) - Static method in class org.apache.mahout.clustering.dirichlet.DirichletDriver
Convenience method provides default Configuration Iterate over the input vectors to produce clusters and, if requested, use the results of the final iteration to cluster the input vectors.
run(String[]) - Method in class org.apache.mahout.clustering.fuzzykmeans.FuzzyKMeansDriver
 
run(Path, Path, Path, DistanceMeasure, double, int, float, boolean, boolean, double, boolean) - Static method in class org.apache.mahout.clustering.fuzzykmeans.FuzzyKMeansDriver
Iterate over the input vectors to produce clusters and, if requested, use the results of the final iteration to cluster the input vectors.
run(Configuration, Path, Path, Path, DistanceMeasure, double, int, float, boolean, boolean, double, boolean) - Static method in class org.apache.mahout.clustering.fuzzykmeans.FuzzyKMeansDriver
Iterate over the input vectors to produce clusters and, if requested, use the results of the final iteration to cluster the input vectors.
run(String[]) - Method in class org.apache.mahout.clustering.kmeans.KMeansDriver
 
run(Configuration, Path, Path, Path, DistanceMeasure, double, int, boolean, boolean) - Static method in class org.apache.mahout.clustering.kmeans.KMeansDriver
Iterate over the input vectors to produce clusters and, if requested, use the results of the final iteration to cluster the input vectors.
run(Path, Path, Path, DistanceMeasure, double, int, boolean, boolean) - Static method in class org.apache.mahout.clustering.kmeans.KMeansDriver
Iterate over the input vectors to produce clusters and, if requested, use the results of the final iteration to cluster the input vectors.
run(Reducer<DoubleWritable, DoubleWritable, DoubleWritable, DoubleWritable>.Context) - Method in class org.apache.mahout.clustering.lda.cvb.CVB0Driver.DualDoubleSumReducer
 
run(String[]) - Method in class org.apache.mahout.clustering.lda.cvb.CVB0Driver
 
run(Configuration, Path, Path, int, int, double, double, int, int, double, Path, Path, Path, long, float, int, int, int, int, boolean) - Static method in class org.apache.mahout.clustering.lda.cvb.CVB0Driver
 
run(String[]) - Method in class org.apache.mahout.clustering.lda.cvb.InMemoryCollapsedVariationalBayes0
 
run(String[]) - Method in class org.apache.mahout.clustering.lda.LDADriver
 
run(Configuration, Path, Path, int, int, double, int, boolean) - Method in class org.apache.mahout.clustering.lda.LDADriver
 
run(String[]) - Method in class org.apache.mahout.clustering.meanshift.MeanShiftCanopyDriver
 
run(Configuration, Path, Path, DistanceMeasure, IKernelProfile, double, double, double, int, boolean, boolean, boolean) - Static method in class org.apache.mahout.clustering.meanshift.MeanShiftCanopyDriver
Run the job where the input format can be either Vectors or Canopies.
run(String[]) - Method in class org.apache.mahout.clustering.minhash.MinHashDriver
 
run(String[]) - Method in class org.apache.mahout.clustering.spectral.eigencuts.EigencutsDriver
 
run(Configuration, Path, Path, int, int, double, double, double) - Static method in class org.apache.mahout.clustering.spectral.eigencuts.EigencutsDriver
Run the Eigencuts clustering algorithm using the supplied arguments
run(String[]) - Method in class org.apache.mahout.clustering.spectral.kmeans.SpectralKMeansDriver
 
run(Configuration, Path, Path, int, int, DistanceMeasure, double, int) - Static method in class org.apache.mahout.clustering.spectral.kmeans.SpectralKMeansDriver
Run the Spectral KMeans clustering on the supplied arguments
run(String[]) - Method in class org.apache.mahout.clustering.topdown.postprocessor.ClusterOutputPostProcessorDriver
CLI to run clustering post processor.
run(Path, Path, boolean) - Static method in class org.apache.mahout.clustering.topdown.postprocessor.ClusterOutputPostProcessorDriver
Post processes the output of clustering algorithms and groups them into respective clusters.
run(String[]) - Method in class org.apache.mahout.fpm.pfpgrowth.FPGrowthDriver
Run TopK FPGrowth given the input file,
run(String[]) - Method in class org.apache.mahout.graph.AdjacencyMatrixJob
 
run(String[]) - Method in class org.apache.mahout.math.hadoop.decomposer.DistributedLanczosSolver.DistributedLanczosSolverJob
 
run(String[]) - Method in class org.apache.mahout.math.hadoop.decomposer.DistributedLanczosSolver
 
run(Path, Path, Path, Path, int, int, boolean, int, double, double, boolean) - Method in class org.apache.mahout.math.hadoop.decomposer.DistributedLanczosSolver
Run the solver to produce raw eigenvectors, then run the EigenVerificationJob to clean them
run(Path, Path, Path, Path, int, int, boolean, int) - Method in class org.apache.mahout.math.hadoop.decomposer.DistributedLanczosSolver
Run the solver to produce the raw eigenvectors
run(String[]) - Method in class org.apache.mahout.math.hadoop.decomposer.EigenVerificationJob
 
run(Path, Path, Path, Path, double, double, boolean, Configuration) - Method in class org.apache.mahout.math.hadoop.decomposer.EigenVerificationJob
Run the job with the given arguments
run(String[]) - Method in class org.apache.mahout.math.hadoop.MatrixMultiplicationJob
 
run(String[]) - Method in class org.apache.mahout.math.hadoop.similarity.cooccurrence.RowSimilarityJob
 
run(String[]) - Method in class org.apache.mahout.math.hadoop.similarity.VectorDistanceSimilarityJob
 
run(Configuration, Path, Path, Path, DistanceMeasure, String) - Static method in class org.apache.mahout.math.hadoop.similarity.VectorDistanceSimilarityJob
 
run(String[]) - Method in class org.apache.mahout.math.hadoop.solver.DistributedConjugateGradientSolver.DistributedConjugateGradientSolverJob
 
run(String[]) - Method in class org.apache.mahout.math.hadoop.solver.DistributedConjugateGradientSolver
 
run(Configuration, Path[], Path, Path, int, int, int, int, int, int, boolean) - Static method in class org.apache.mahout.math.hadoop.stochasticsvd.ABtDenseOutJob
 
run(Configuration, Path[], Path, Path, int, int, int, int, int, int, boolean) - Static method in class org.apache.mahout.math.hadoop.stochasticsvd.ABtJob
 
run(Configuration, Path[], Path, Path, int, int, int, int, int, boolean, Class<? extends Writable>, boolean) - Static method in class org.apache.mahout.math.hadoop.stochasticsvd.BtJob
 
run(Configuration, Path[], Path, int, int, int, int, long, int) - Static method in class org.apache.mahout.math.hadoop.stochasticsvd.QJob
 
run(String[]) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.SSVDCli
 
run() - Method in class org.apache.mahout.math.hadoop.stochasticsvd.SSVDSolver
run all SSVD jobs.
run(Configuration, Path[], Path, int, int, long) - Static method in class org.apache.mahout.math.hadoop.stochasticsvd.YtYJob
 
run(String[]) - Method in class org.apache.mahout.math.hadoop.TransposeJob
 
run(String[]) - Method in class org.apache.mahout.math.stats.entropy.ConditionalEntropy
 
run(String[]) - Method in class org.apache.mahout.math.stats.entropy.Entropy
 
run(String[]) - Method in class org.apache.mahout.math.stats.entropy.InformationGain
 
run(String[]) - Method in class org.apache.mahout.math.stats.entropy.InformationGainRatio
 
run(String[]) - Method in class org.apache.mahout.vectorizer.collocations.llr.CollocDriver
 
run(String[]) - Method in class org.apache.mahout.vectorizer.EncodedVectorsFromSequenceFiles
 
run(String[]) - Method in class org.apache.mahout.vectorizer.SparseVectorsFromSequenceFiles
 
runFuzzyKMeansIteration(Iterable<Vector>, List<SoftCluster>, FuzzyKMeansClusterer) - Static method in class org.apache.mahout.clustering.fuzzykmeans.FuzzyKMeansClusterer
Perform a single iteration over the points and clusters, assigning points to clusters and returning if the iterations are completed.
runIteration(Configuration, Path, Path, Path, int, int, int) - Static method in class org.apache.mahout.clustering.lda.cvb.CVB0Driver
 
runJob(Parameters) - Static method in class org.apache.mahout.classifier.bayes.mapreduce.bayes.BayesClassifierDriver
Run the job
runJob(Path, Path, BayesParameters) - Method in class org.apache.mahout.classifier.bayes.mapreduce.bayes.BayesDriver
 
runJob(Path, Path, BayesParameters) - Method in class org.apache.mahout.classifier.bayes.mapreduce.bayes.BayesThetaNormalizerDriver
 
runJob(Path, Path, BayesParameters) - Method in class org.apache.mahout.classifier.bayes.mapreduce.cbayes.CBayesDriver
 
runJob(Path, Path, BayesParameters) - Method in class org.apache.mahout.classifier.bayes.mapreduce.cbayes.CBayesThetaNormalizerDriver
 
runJob(Path, Path, BayesParameters) - Method in class org.apache.mahout.classifier.bayes.mapreduce.common.BayesFeatureDriver
 
runJob(Path, Path, BayesParameters) - Method in interface org.apache.mahout.classifier.bayes.mapreduce.common.BayesJob
Execute a classification job on a cluster.
runJob(Path, Path, BayesParameters) - Method in class org.apache.mahout.classifier.bayes.mapreduce.common.BayesTfIdfDriver
 
runJob(Path, Path, BayesParameters) - Method in class org.apache.mahout.classifier.bayes.mapreduce.common.BayesWeightSummerDriver
 
runJob(Job) - Method in class org.apache.mahout.classifier.df.mapreduce.Builder
Sequential implementation should override this method to simulate the job execution
runJob(Path, Path, int, int) - Static method in class org.apache.mahout.clustering.spectral.common.AffinityMatrixInputJob
Initializes and executes the job of reading the documents containing the data of the affinity matrix in (x_i, x_j, value) format.
runJob(Path, Path, int) - Static method in class org.apache.mahout.clustering.spectral.common.AffinityMatrixInputJob
A transparent wrapper for the above method which handles the tedious tasks of setting and retrieving system Paths.
runJob(Path, int) - Static method in class org.apache.mahout.clustering.spectral.common.MatrixDiagonalizeJob
 
runJob(Path, Path) - Static method in class org.apache.mahout.clustering.spectral.common.UnitVectorizerJob
 
runJob(Path, Vector, Path) - Static method in class org.apache.mahout.clustering.spectral.common.VectorMatrixMultiplicationJob
Invokes the job.
runJob(Path, Vector, Path, Path) - Static method in class org.apache.mahout.clustering.spectral.common.VectorMatrixMultiplicationJob
 
runjob(Path, Path, Path, Configuration) - Static method in class org.apache.mahout.clustering.spectral.eigencuts.EigencutsAffinityCutsJob
Runs a single iteration of defining cluster boundaries, based on previous calculations and the formation of the "cut matrix".
runJob(Vector, Vector, Path, double, double, double, double, Path) - Static method in class org.apache.mahout.clustering.spectral.eigencuts.EigencutsSensitivityJob
Initializes the configuration tasks, loads the needed data into the HDFS cache, and executes the job.
runJob(Configuration, LanczosState, int, boolean, String) - Method in class org.apache.mahout.math.hadoop.decomposer.DistributedLanczosSolver
 
runJob(Configuration, Path, Path, int, int, boolean, int, String) - Method in class org.apache.mahout.math.hadoop.decomposer.DistributedLanczosSolver
Factored-out LanczosSolver for the purpose of invoking it programmatically
runJob(Configuration, Path, Path, Path, boolean, double, int) - Method in class org.apache.mahout.math.hadoop.decomposer.EigenVerificationJob
Progammatic invocation of run()
runJob(Path, Path, int, int, Vector, Preconditioner, int, double) - Method in class org.apache.mahout.math.hadoop.solver.DistributedConjugateGradientSolver
Runs the distributed conjugate gradient solver programmatically to solve the system (A + lambda*I)x = b.
runKMeansIteration(Iterable<Vector>, Iterable<Cluster>, DistanceMeasure, double) - Static method in class org.apache.mahout.clustering.kmeans.KMeansClusterer
Perform a single iteration over the points and clusters, assigning points to clusters and returning if the iterations are completed.
runLoad(Recommender) - Static method in class org.apache.mahout.cf.taste.impl.eval.LoadEvaluator
 
runLoad(Recommender, int) - Static method in class org.apache.mahout.cf.taste.impl.eval.LoadEvaluator
 
RunningAverage - Interface in org.apache.mahout.cf.taste.impl.common
Interface for classes that can keep track of a running average of a series of numbers.
RunningAverageAndStdDev - Interface in org.apache.mahout.cf.taste.impl.common
Extends RunningAverage by adding standard deviation too.
RunningSumsGaussianAccumulator - Class in org.apache.mahout.clustering
An online Gaussian accumulator that uses a running power sums approach as reported on http://en.wikipedia.org/wiki/Standard_deviation Suffers from overflow, underflow and roundoff error but has minimal observe-time overhead
RunningSumsGaussianAccumulator() - Constructor for class org.apache.mahout.clustering.RunningSumsGaussianAccumulator
 
runPFPGrowth(Parameters) - Static method in class org.apache.mahout.fpm.pfpgrowth.PFPGrowth
 

S

sample(Vector, int) - Method in class org.apache.mahout.clustering.lda.LDASampler
 
sample(Vector) - Method in class org.apache.mahout.math.stats.Sampler
 
sample() - Method in class org.apache.mahout.math.stats.Sampler
 
SAMPLE_SIZE - Static variable in class org.apache.mahout.cf.taste.hadoop.preparation.ToItemVectorsMapper
 
sampleFromPosterior() - Method in class org.apache.mahout.clustering.dirichlet.DirichletCluster
 
sampleFromPosterior(Model<VectorWritable>[]) - Method in class org.apache.mahout.clustering.dirichlet.models.DistanceMeasureClusterDistribution
 
sampleFromPosterior() - Method in class org.apache.mahout.clustering.dirichlet.models.GaussianCluster
 
sampleFromPosterior(Model<VectorWritable>[]) - Method in class org.apache.mahout.clustering.dirichlet.models.GaussianClusterDistribution
 
sampleFromPosterior() - Method in class org.apache.mahout.clustering.DistanceMeasureCluster
 
sampleFromPosterior() - Method in interface org.apache.mahout.clustering.Model
 
sampleFromPosterior(Model<O>[]) - Method in interface org.apache.mahout.clustering.ModelDistribution
Return a list of models sampled from the posterior
sampleFromPrior(int) - Method in class org.apache.mahout.clustering.dirichlet.models.DistanceMeasureClusterDistribution
 
sampleFromPrior(int) - Method in class org.apache.mahout.clustering.dirichlet.models.GaussianClusterDistribution
 
sampleFromPrior(int) - Method in interface org.apache.mahout.clustering.ModelDistribution
Return a list of models sampled from the prior
samplePosteriorModels() - Method in class org.apache.mahout.clustering.dirichlet.DirichletClusterer
 
Sampler - Class in org.apache.mahout.math.stats
Discrete distribution sampler: Samples from a given discrete distribution: you provide a source of randomness and a Vector (cardinality N) which describes a distribution over [0,N), and calls to sample() sample from 0 to N using this distribution
Sampler(Random) - Constructor for class org.apache.mahout.math.stats.Sampler
 
Sampler(Random, double[]) - Constructor for class org.apache.mahout.math.stats.Sampler
 
Sampler(Random, Vector) - Constructor for class org.apache.mahout.math.stats.Sampler
 
sampleTerm(Vector) - Method in class org.apache.mahout.clustering.lda.cvb.TopicModel
 
sampleTerm(int) - Method in class org.apache.mahout.clustering.lda.cvb.TopicModel
 
SamplingCandidateItemsStrategy - Class in org.apache.mahout.cf.taste.impl.recommender
Returns all items that have not been rated by the user (3) and that were preferred by another user (2) that has preferred at least one item (1) that the current user has preferred too.
SamplingCandidateItemsStrategy(int, int) - Constructor for class org.apache.mahout.cf.taste.impl.recommender.SamplingCandidateItemsStrategy
Defaults to using no limit (SamplingCandidateItemsStrategy.NO_LIMIT_FACTOR) for all factors, except candidatesPerUserFactor which defaults to SamplingCandidateItemsStrategy.DEFAULT_FACTOR.
SamplingCandidateItemsStrategy(int, int, int, int, int) - Constructor for class org.apache.mahout.cf.taste.impl.recommender.SamplingCandidateItemsStrategy
 
SamplingIterable<T> - Class in org.apache.mahout.common.iterator
Wraps an Iterable whose Iterable.iterator() returns only some subset of the elements that it would, as determined by a iterator rate parameter.
SamplingIterable(Iterable<? extends T>, double) - Constructor for class org.apache.mahout.common.iterator.SamplingIterable
 
SamplingIterator<T> - Class in org.apache.mahout.common.iterator
Wraps an Iterator and returns only some subset of the elements that it would, as determined by a iterator rate parameter.
SamplingIterator(Iterator<? extends T>, double) - Constructor for class org.apache.mahout.common.iterator.SamplingIterator
 
SamplingLongPrimitiveIterator - Class in org.apache.mahout.cf.taste.impl.common
Wraps a LongPrimitiveIterator and returns only some subset of the elements that it would, as determined by a sampling rate parameter.
SamplingLongPrimitiveIterator(LongPrimitiveIterator, double) - Constructor for class org.apache.mahout.cf.taste.impl.common.SamplingLongPrimitiveIterator
 
save(Writable, Vector, Path, Configuration, boolean, boolean) - Static method in class org.apache.mahout.clustering.spectral.common.VectorCache
 
save(Writable, Vector, Path, Configuration) - Static method in class org.apache.mahout.clustering.spectral.common.VectorCache
Calls the save() method, setting the cache to overwrite any previous Path and to delete the path after exiting
saveFList(Iterable<Pair<String, Long>>, Parameters, Configuration) - Static method in class org.apache.mahout.fpm.pfpgrowth.PFPGrowth
Serializes the fList and returns the string representation of the List
scale(VectorWritable) - Method in class org.apache.mahout.math.hadoop.TimesSquaredJob.TimesSquaredMapper
 
SEEDS - Static variable in class org.apache.mahout.math.hadoop.similarity.VectorDistanceSimilarityJob
 
SEEDS_PATH_KEY - Static variable in class org.apache.mahout.math.hadoop.similarity.VectorDistanceSimilarityJob
 
select(Vector) - Method in interface org.apache.mahout.clustering.ClusteringPolicy
Return the index of the most appropriate model
select(Vector) - Method in class org.apache.mahout.clustering.DirichletClusteringPolicy
 
select(Vector) - Method in class org.apache.mahout.clustering.FuzzyKMeansClusteringPolicy
 
select(Vector) - Method in class org.apache.mahout.clustering.KMeansClusteringPolicy
 
SequenceFileDirIterable<K extends org.apache.hadoop.io.Writable,V extends org.apache.hadoop.io.Writable> - Class in org.apache.mahout.common.iterator.sequencefile
Iterable counterpart to SequenceFileDirIterator.
SequenceFileDirIterable(Path, PathType, Configuration) - Constructor for class org.apache.mahout.common.iterator.sequencefile.SequenceFileDirIterable
 
SequenceFileDirIterable(Path, PathType, PathFilter, Configuration) - Constructor for class org.apache.mahout.common.iterator.sequencefile.SequenceFileDirIterable
 
SequenceFileDirIterable(Path, PathType, PathFilter, Comparator<FileStatus>, boolean, Configuration) - Constructor for class org.apache.mahout.common.iterator.sequencefile.SequenceFileDirIterable
 
SequenceFileDirIterator<K extends org.apache.hadoop.io.Writable,V extends org.apache.hadoop.io.Writable> - Class in org.apache.mahout.common.iterator.sequencefile
Like SequenceFileIterator, but iterates not just over one sequence file, but many.
SequenceFileDirIterator(Path[], boolean, Configuration) - Constructor for class org.apache.mahout.common.iterator.sequencefile.SequenceFileDirIterator
Multifile sequence file iterator where files are specified explicitly by path parameters.
SequenceFileDirIterator(Path, PathType, PathFilter, Comparator<FileStatus>, boolean, Configuration) - Constructor for class org.apache.mahout.common.iterator.sequencefile.SequenceFileDirIterator
Constructor that uses either FileSystem.listStatus(Path) or FileSystem.globStatus(Path) to obtain list of files to iterate over (depending on pathType parameter).
SequenceFileDirValueIterable<V extends org.apache.hadoop.io.Writable> - Class in org.apache.mahout.common.iterator.sequencefile
Iterable counterpart to SequenceFileDirValueIterator.
SequenceFileDirValueIterable(Path, PathType, Configuration) - Constructor for class org.apache.mahout.common.iterator.sequencefile.SequenceFileDirValueIterable
 
SequenceFileDirValueIterable(Path, PathType, PathFilter, Configuration) - Constructor for class org.apache.mahout.common.iterator.sequencefile.SequenceFileDirValueIterable
 
SequenceFileDirValueIterable(Path, PathType, PathFilter, Comparator<FileStatus>, boolean, Configuration) - Constructor for class org.apache.mahout.common.iterator.sequencefile.SequenceFileDirValueIterable
 
SequenceFileDirValueIterator<V extends org.apache.hadoop.io.Writable> - Class in org.apache.mahout.common.iterator.sequencefile
Like SequenceFileValueIterator, but iterates not just over one sequence file, but many.
SequenceFileDirValueIterator(Path, PathType, PathFilter, Comparator<FileStatus>, boolean, Configuration) - Constructor for class org.apache.mahout.common.iterator.sequencefile.SequenceFileDirValueIterator
Constructor that uses either FileSystem.listStatus(Path) or FileSystem.globStatus(Path) to obtain list of files to iterate over (depending on pathType parameter).
SequenceFileDirValueIterator(Path[], Comparator<FileStatus>, boolean, Configuration) - Constructor for class org.apache.mahout.common.iterator.sequencefile.SequenceFileDirValueIterator
Multifile sequence file iterator where files are specified explicitly by path parameters.
SequenceFileIterable<K extends org.apache.hadoop.io.Writable,V extends org.apache.hadoop.io.Writable> - Class in org.apache.mahout.common.iterator.sequencefile
Iterable counterpart to SequenceFileIterator.
SequenceFileIterable(Path, Configuration) - Constructor for class org.apache.mahout.common.iterator.sequencefile.SequenceFileIterable
Like SequenceFileIterable.SequenceFileIterable(Path, boolean, Configuration) but key and value instances are not reused by default.
SequenceFileIterable(Path, boolean, Configuration) - Constructor for class org.apache.mahout.common.iterator.sequencefile.SequenceFileIterable
 
SequenceFileIterator<K extends org.apache.hadoop.io.Writable,V extends org.apache.hadoop.io.Writable> - Class in org.apache.mahout.common.iterator.sequencefile
Iterator over a SequenceFile's keys and values, as a Pair containing key and value.
SequenceFileIterator(Path, boolean, Configuration) - Constructor for class org.apache.mahout.common.iterator.sequencefile.SequenceFileIterator
 
SequenceFileModelReader - Class in org.apache.mahout.classifier.bayes
This Class reads the different interim files created during the Training stage as well as the Model File during testing.
SequenceFileOutputCollector<K extends org.apache.hadoop.io.Writable,V extends org.apache.hadoop.io.Writable> - Class in org.apache.mahout.fpm.pfpgrowth.convertors
Collects the Writable key and Writable value, and writes them into a SequenceFile
SequenceFileOutputCollector(SequenceFile.Writer) - Constructor for class org.apache.mahout.fpm.pfpgrowth.convertors.SequenceFileOutputCollector
 
SequenceFileTokenizerMapper - Class in org.apache.mahout.vectorizer.document
Tokenizes a text document and outputs tokens in a StringTuple
SequenceFileTokenizerMapper() - Constructor for class org.apache.mahout.vectorizer.document.SequenceFileTokenizerMapper
 
SequenceFileValueIterable<V extends org.apache.hadoop.io.Writable> - Class in org.apache.mahout.common.iterator.sequencefile
Iterable counterpart to SequenceFileValueIterator.
SequenceFileValueIterable(Path, Configuration) - Constructor for class org.apache.mahout.common.iterator.sequencefile.SequenceFileValueIterable
Like SequenceFileValueIterable.SequenceFileValueIterable(Path, boolean, Configuration) but instances are not reused by default.
SequenceFileValueIterable(Path, boolean, Configuration) - Constructor for class org.apache.mahout.common.iterator.sequencefile.SequenceFileValueIterable
 
SequenceFileValueIterator<V extends org.apache.hadoop.io.Writable> - Class in org.apache.mahout.common.iterator.sequencefile
Iterator over a SequenceFile's values only.
SequenceFileValueIterator(Path, boolean, Configuration) - Constructor for class org.apache.mahout.common.iterator.sequencefile.SequenceFileValueIterator
 
SEQUENTIAL_ACCESS - Static variable in class org.apache.mahout.vectorizer.common.PartialVectorMerger
 
SEQUENTIAL_METHOD - Static variable in class org.apache.mahout.common.commandline.DefaultOptionCreator
 
SequentialBuilder - Class in org.apache.mahout.classifier.df.ref
Builds a Random Decision Forest using a given TreeBuilder to grow the trees
SequentialBuilder(Random, TreeBuilder, Data) - Constructor for class org.apache.mahout.classifier.df.ref.SequentialBuilder
Constructor
SequentialOutOfCoreSvd - Class in org.apache.mahout.math.ssvd
Sequential block-oriented out of core SVD algorithm.
SequentialOutOfCoreSvd(Iterable<File>, File, int, int) - Constructor for class org.apache.mahout.math.ssvd.SequentialOutOfCoreSvd
 
serialize(Path, Configuration) - Method in class org.apache.mahout.classifier.naivebayes.NaiveBayesModel
 
serializeOutput(LanczosState, Path) - Method in class org.apache.mahout.math.hadoop.decomposer.DistributedLanczosSolver
 
set(long, int) - Method in class org.apache.mahout.cf.taste.hadoop.EntityCountWritable
 
set(long, long) - Method in class org.apache.mahout.cf.taste.hadoop.EntityEntityWritable
 
set(long, float) - Method in class org.apache.mahout.cf.taste.hadoop.EntityPrefWritable
 
set(float, Vector) - Method in class org.apache.mahout.cf.taste.hadoop.item.PrefAndSimilarityColumnWritable
 
set(Vector) - Method in class org.apache.mahout.cf.taste.hadoop.item.VectorOrPrefWritable
 
set(long, float) - Method in class org.apache.mahout.cf.taste.hadoop.item.VectorOrPrefWritable
 
set(List<RecommendedItem>) - Method in class org.apache.mahout.cf.taste.hadoop.RecommendedItemsWritable
 
set(int, Preference) - Method in class org.apache.mahout.cf.taste.impl.model.BooleanItemPreferenceArray
 
set(int, Preference) - Method in class org.apache.mahout.cf.taste.impl.model.BooleanUserPreferenceArray
 
set(int, Preference) - Method in class org.apache.mahout.cf.taste.impl.model.GenericItemPreferenceArray
 
set(int, Preference) - Method in class org.apache.mahout.cf.taste.impl.model.GenericUserPreferenceArray
 
set(int, Preference) - Method in interface org.apache.mahout.cf.taste.model.PreferenceArray
Sets preference at i from information in the given Preference
set(int, double) - Method in class org.apache.mahout.classifier.df.data.Instance
Set the value at the given index
set(int, int) - Method in class org.apache.mahout.classifier.df.mapreduce.partial.TreeID
 
set(int, int) - Method in class org.apache.mahout.common.IntPairWritable
 
set(T) - Method in class org.apache.mahout.common.parameters.AbstractParameter
 
set(T) - Method in interface org.apache.mahout.common.parameters.Parameter
 
set(String, String) - Method in class org.apache.mahout.common.Parameters
 
set(K, V) - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.LeastKCache
 
set(Matrix) - Method in class org.apache.mahout.math.MatrixWritable
 
set(int) - Method in class org.apache.mahout.math.VarIntWritable
 
set(long) - Method in class org.apache.mahout.math.VarLongWritable
 
set(Vector) - Method in class org.apache.mahout.math.VectorWritable
 
set(Gram, byte[]) - Method in class org.apache.mahout.vectorizer.collocations.llr.GramKey
set the gram held by this key
setAbtBlockHeight(int) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.SSVDSolver
the block height of Y_i during power iterations.
setAnalyzer(Analyzer) - Method in class org.apache.mahout.vectorizer.encoders.LuceneTextValueEncoder
 
setAnalyzerClassName(String) - Method in class org.apache.mahout.vectorizer.VectorizerConfig
 
setAucEvaluator(OnlineAuc) - Method in class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression
 
setAucEvaluator(OnlineAuc) - Method in class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression.Wrapper
 
setAucEvaluator(OnlineAuc) - Method in class org.apache.mahout.classifier.sgd.CrossFoldLearner
 
setAveragingWindow(int) - Method in class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression
 
setBasePath(String) - Method in class org.apache.mahout.classifier.bayes.BayesParameters
 
setBest(State<AdaptiveLogisticRegression.Wrapper, CrossFoldLearner>) - Method in class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression
 
setBeta(int, int, double) - Method in class org.apache.mahout.classifier.sgd.AbstractOnlineLogisticRegression
 
setBlock(double[][]) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.DenseBlockWritable
 
setBoundPoints(IntArrayList) - Method in class org.apache.mahout.clustering.meanshift.MeanShiftCanopy
 
setBroadcast(boolean) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.SSVDSolver
If this property is true, use DestributedCache mechanism to broadcast some stuff around.
setBuffer(List<AdaptiveLogisticRegression.TrainingExample>) - Method in class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression
 
setCardinality(int) - Method in class org.apache.mahout.vectorizer.VectorizerConfig
 
setCenter(Vector) - Method in class org.apache.mahout.clustering.AbstractCluster
 
setChunkSizeInMegabytes(int) - Method in class org.apache.mahout.vectorizer.VectorizerConfig
 
setClusteredPoints(Path) - Method in class org.apache.mahout.clustering.topdown.postprocessor.ClusterOutputPostProcessor
 
setClusters(List<DirichletCluster>) - Method in class org.apache.mahout.clustering.dirichlet.DirichletState
 
setCol(int) - Method in class org.apache.mahout.clustering.spectral.common.VertexWritable
 
setCol(int) - Method in class org.apache.mahout.math.hadoop.DistributedRowMatrix.MatrixEntryWritable
 
setComplemented(boolean) - Method in class org.apache.mahout.classifier.df.builder.DecisionTreeBuilder
 
setComputeU(boolean) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.SSVDSolver
The setting controlling whether to compute U matrix of low rank SSVD.
setComputeV(boolean) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.SSVDSolver
Setting controlling whether to compute V matrix of low-rank SSVD.
setConditional(int, int) - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.FPTree
 
setConf(Configuration) - Method in class org.apache.mahout.clustering.lda.cvb.TopicModel
 
setConf(Configuration) - Method in class org.apache.mahout.math.hadoop.decomposer.DistributedLanczosSolver.DistributedLanczosSolverJob
 
setConf(Configuration) - Method in class org.apache.mahout.math.hadoop.decomposer.DistributedLanczosSolver
 
setConf(Configuration) - Method in class org.apache.mahout.math.hadoop.decomposer.HdfsBackedLanczosState
 
setConf(Configuration) - Method in class org.apache.mahout.math.hadoop.DistributedRowMatrix
 
setConf(Configuration) - Method in class org.apache.mahout.math.hadoop.solver.DistributedConjugateGradientSolver.DistributedConjugateGradientSolverJob
 
setConf(Configuration) - Method in class org.apache.mahout.math.hadoop.solver.DistributedConjugateGradientSolver
 
setConf(Configuration) - Method in class org.apache.mahout.vectorizer.VectorizerConfig
 
setConverged(boolean) - Method in class org.apache.mahout.clustering.kmeans.Cluster
 
setCovarianceMatrix(Matrix) - Method in class org.apache.mahout.common.distance.MahalanobisDistanceMeasure
Computes the inverse covariance from the input covariance matrix given in input.
setcUHalfSigma(boolean) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.SSVDSolver
 
setcVHalfSigma(boolean) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.SSVDSolver
 
setDictionary(Map<String, Double>) - Method in class org.apache.mahout.vectorizer.encoders.StaticWordValueEncoder
Sets the weighting dictionary to be used by this encoder.
setEigensToVerify(VectorIterable) - Method in class org.apache.mahout.math.hadoop.decomposer.EigenVerificationJob
 
setEncoderClass(String) - Method in class org.apache.mahout.vectorizer.VectorizerConfig
 
setEncoderName(String) - Method in class org.apache.mahout.vectorizer.VectorizerConfig
 
setEp(EvolutionaryProcess<AdaptiveLogisticRegression.Wrapper, CrossFoldLearner>) - Method in class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression
 
setExponent(double) - Method in class org.apache.mahout.common.distance.MinkowskiDistanceMeasure
 
setFirst(int) - Method in class org.apache.mahout.common.IntPairWritable
 
setFreezeSurvivors(boolean) - Method in class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression
 
setFrequency(int) - Method in class org.apache.mahout.vectorizer.collocations.llr.Gram
 
setGradient(Gradient) - Method in class org.apache.mahout.classifier.sgd.AbstractOnlineLogisticRegression
 
setGramSize(int) - Method in class org.apache.mahout.classifier.bayes.BayesParameters
 
setId(int) - Method in class org.apache.mahout.clustering.AbstractCluster
 
setId(int) - Method in class org.apache.mahout.ep.State
 
setIdName(String) - Method in class org.apache.mahout.classifier.sgd.CsvRecordFactory
 
setIgSplit(IgSplit) - Method in class org.apache.mahout.classifier.df.builder.DecisionTreeBuilder
 
setInstances(double[][]) - Method in class org.apache.mahout.classifier.RegressionResultAnalyzer
 
setInterval(int) - Method in class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression
How often should the evolutionary optimization of learning parameters occur?
setInterval(int, int) - Method in class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression
Starts optimization using the shorter interval and progresses to the longer using the specified number of steps per decade.
setInverseCovarianceMatrix(Matrix) - Method in class org.apache.mahout.common.distance.MahalanobisDistanceMeasure
 
setItemID(int, long) - Method in class org.apache.mahout.cf.taste.impl.model.BooleanItemPreferenceArray
Sets item ID for preference at i.
setItemID(int, long) - Method in class org.apache.mahout.cf.taste.impl.model.BooleanUserPreferenceArray
 
setItemID(int, long) - Method in class org.apache.mahout.cf.taste.impl.model.GenericItemPreferenceArray
Sets item ID for preference at i.
setItemID(int, long) - Method in class org.apache.mahout.cf.taste.impl.model.GenericUserPreferenceArray
 
setItemID(int, long) - Method in interface org.apache.mahout.cf.taste.model.PreferenceArray
Sets item ID for preference at i.
setIterationNumber(int) - Method in class org.apache.mahout.math.hadoop.decomposer.HdfsBackedLanczosState
 
setKey(int) - Method in class org.apache.mahout.clustering.spectral.common.IntDoublePairWritable
 
setLabel(String) - Method in class org.apache.mahout.classifier.ClassifierResult
 
setLabels(int[]) - Method in class org.apache.mahout.math.MultiLabelVectorWritable
 
setLogLikelihood(double) - Method in class org.apache.mahout.classifier.ClassifierResult
 
setLogLikelihood(double) - Method in class org.apache.mahout.classifier.sgd.CrossFoldLearner
 
setLogLikelihood(double) - Method in class org.apache.mahout.clustering.lda.LDAState
 
setLogNormalize(boolean) - Method in class org.apache.mahout.vectorizer.VectorizerConfig
 
setM(int) - Method in class org.apache.mahout.classifier.df.builder.DecisionTreeBuilder
 
setM(int) - Method in class org.apache.mahout.classifier.df.builder.DefaultTreeBuilder
 
setMap(int, Mapping) - Method in class org.apache.mahout.ep.State
Defines the transformation for a parameter.
setMappings(State<AdaptiveLogisticRegression.Wrapper, CrossFoldLearner>) - Method in class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression.Wrapper
 
setMaps(Mapping[]) - Method in class org.apache.mahout.ep.State
 
setMaps(Iterable<Mapping>) - Method in class org.apache.mahout.ep.State
 
setMatrix(Matrix) - Method in class org.apache.mahout.classifier.ConfusionMatrix
 
setMaxBufferSize(int) - Method in class org.apache.mahout.classifier.evaluation.Auc
 
setMaxNGramSize(int) - Method in class org.apache.mahout.vectorizer.VectorizerConfig
 
setMaxPreference(float) - Method in interface org.apache.mahout.cf.taste.eval.RecommenderEvaluator
Deprecated. 
setMaxPreference(float) - Method in class org.apache.mahout.cf.taste.impl.eval.AbstractDifferenceRecommenderEvaluator
 
setMaxPreference(float) - Method in class org.apache.mahout.cf.taste.impl.model.AbstractDataModel
 
setMeanVector(Vector) - Method in class org.apache.mahout.common.distance.MahalanobisDistanceMeasure
 
setMeasure(DistanceMeasure) - Method in class org.apache.mahout.clustering.dirichlet.models.DistanceMeasureClusterDistribution
 
setMeasure(DistanceMeasure) - Method in class org.apache.mahout.clustering.DistanceMeasureCluster
 
setMinDF(int) - Method in class org.apache.mahout.classifier.bayes.BayesParameters
 
setMinLLRValue(float) - Method in class org.apache.mahout.vectorizer.VectorizerConfig
 
setMinPreference(float) - Method in interface org.apache.mahout.cf.taste.eval.RecommenderEvaluator
Deprecated. 
setMinPreference(float) - Method in class org.apache.mahout.cf.taste.impl.eval.AbstractDifferenceRecommenderEvaluator
 
setMinPreference(float) - Method in class org.apache.mahout.cf.taste.impl.model.AbstractDataModel
 
setMinSplitNum(int) - Method in class org.apache.mahout.classifier.df.builder.DecisionTreeBuilder
 
setMinSplitSize(int) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.SSVDSolver
Sometimes, if requested A blocks become larger than a split, we may need to use that to ensure at least k+p rows of A get into a split.
setMinSupport(int) - Method in class org.apache.mahout.classifier.bayes.BayesParameters
 
setMinSupport(int) - Method in class org.apache.mahout.vectorizer.VectorizerConfig
 
setMinVarianceProportion(double) - Method in class org.apache.mahout.classifier.df.builder.DecisionTreeBuilder
 
setMissingValueWeight(double) - Method in class org.apache.mahout.vectorizer.encoders.StaticWordValueEncoder
Sets the weight that is to be used for values that do not appear in the dictionary.
setMixture(Vector) - Method in class org.apache.mahout.clustering.dirichlet.DirichletState
 
setModel(Cluster) - Method in class org.apache.mahout.clustering.dirichlet.DirichletCluster
 
setModelFactory(ModelDistribution<VectorWritable>) - Method in class org.apache.mahout.clustering.dirichlet.DirichletState
 
setModelPrototype(VectorWritable) - Method in class org.apache.mahout.clustering.dirichlet.models.AbstractVectorModelDistribution
 
setNamedVectors(boolean) - Method in class org.apache.mahout.vectorizer.VectorizerConfig
 
setNbTrees(Configuration, int) - Static method in class org.apache.mahout.classifier.df.mapreduce.Builder
Set the number of trees to grow for the map-reduce job
setNext(int, int) - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.FPTree
 
setNormPower(float) - Method in class org.apache.mahout.vectorizer.VectorizerConfig
 
setNumClusters(int) - Method in class org.apache.mahout.clustering.dirichlet.DirichletState
 
setNumFeatures(int) - Method in class org.apache.mahout.classifier.sgd.CrossFoldLearner
 
setNumPoints(long) - Method in class org.apache.mahout.clustering.AbstractCluster
 
setNumReducers(int) - Method in class org.apache.mahout.vectorizer.VectorizerConfig
 
setOmni(double) - Method in class org.apache.mahout.ep.State
 
setOuterBlockHeight(int) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.SSVDSolver
The height of outer blocks during Q'A multiplication.
setOutputDirName(String) - Method in class org.apache.mahout.classifier.df.mapreduce.Builder
Sets the Output directory name, will be creating in the working directory
setOutputTempPathString(String) - Method in class org.apache.mahout.math.hadoop.DistributedRowMatrix
 
setOverwrite(boolean) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.SSVDSolver
if true, driver to clean output folder first if exists.
setParameters(double[]) - Method in class org.apache.mahout.classifier.sgd.CrossFoldLearner
 
setParent(int, int) - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.FPTree
 
setPayload(T) - Method in class org.apache.mahout.ep.State
 
setPolicy(GlobalOnlineAuc.ReplacementPolicy) - Method in class org.apache.mahout.math.stats.GlobalOnlineAuc
 
setPolicy(GlobalOnlineAuc.ReplacementPolicy) - Method in class org.apache.mahout.math.stats.GroupedOnlineAuc
 
setPolicy(GlobalOnlineAuc.ReplacementPolicy) - Method in interface org.apache.mahout.math.stats.OnlineAuc
 
setPoolSize(int) - Method in class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression
 
setPreference(long, long, float) - Method in class org.apache.mahout.cf.taste.impl.model.file.FileDataModel
Note that this method only updates the in-memory preference data that this maintains; it does not modify any data on disk.
setPreference(long, long, float) - Method in class org.apache.mahout.cf.taste.impl.model.GenericBooleanPrefDataModel
 
setPreference(long, long, float) - Method in class org.apache.mahout.cf.taste.impl.model.GenericDataModel
 
setPreference(long, long, float) - Method in class org.apache.mahout.cf.taste.impl.model.PlusAnonymousUserDataModel
 
setPreference(long, long, float) - Method in class org.apache.mahout.cf.taste.impl.recommender.AbstractRecommender
Default implementation which just calls DataModel.setPreference(long, long, float).
setPreference(long, long, float) - Method in class org.apache.mahout.cf.taste.impl.recommender.CachingRecommender
 
setPreference(long, long, float) - Method in class org.apache.mahout.cf.taste.impl.recommender.ItemAverageRecommender
 
setPreference(long, long, float) - Method in class org.apache.mahout.cf.taste.impl.recommender.ItemUserAverageRecommender
 
setPreference(long, long, float) - Method in class org.apache.mahout.cf.taste.impl.recommender.slopeone.SlopeOneRecommender
 
setPreference(long, long, float) - Method in interface org.apache.mahout.cf.taste.model.DataModel
Sets a particular preference (item plus rating) for a user.
setPreference(long, long, float) - Method in interface org.apache.mahout.cf.taste.recommender.Recommender
 
setPreferenceInferrer(PreferenceInferrer) - Method in class org.apache.mahout.cf.taste.impl.similarity.CachingUserSimilarity
 
setPreferenceInferrer(PreferenceInferrer) - Method in class org.apache.mahout.cf.taste.impl.similarity.CityBlockSimilarity
 
setPreferenceInferrer(PreferenceInferrer) - Method in class org.apache.mahout.cf.taste.impl.similarity.GenericUserSimilarity
 
setPreferenceInferrer(PreferenceInferrer) - Method in class org.apache.mahout.cf.taste.impl.similarity.LogLikelihoodSimilarity
 
setPreferenceInferrer(PreferenceInferrer) - Method in class org.apache.mahout.cf.taste.impl.similarity.SpearmanCorrelationSimilarity
 
setPreferenceInferrer(PreferenceInferrer) - Method in class org.apache.mahout.cf.taste.impl.similarity.TanimotoCoefficientSimilarity
 
setPreferenceInferrer(PreferenceInferrer) - Method in interface org.apache.mahout.cf.taste.similarity.UserSimilarity
Attaches a PreferenceInferrer to the implementation.
setPrior(PriorFunction) - Method in class org.apache.mahout.classifier.sgd.AbstractOnlineLogisticRegression
 
setPrior(PriorFunction) - Method in class org.apache.mahout.classifier.sgd.CrossFoldLearner
 
setProbabilityScore(boolean) - Method in class org.apache.mahout.classifier.evaluation.Auc
 
setProbes(int) - Method in class org.apache.mahout.vectorizer.encoders.CachingContinuousValueEncoder
 
setProbes(int) - Method in class org.apache.mahout.vectorizer.encoders.CachingStaticWordValueEncoder
 
setProbes(int) - Method in class org.apache.mahout.vectorizer.encoders.CachingValueEncoder
Sets the number of locations in the feature vector that a value should be in.
setProbes(int) - Method in class org.apache.mahout.vectorizer.encoders.FeatureVectorEncoder
Sets the number of locations in the feature vector that a value should be in.
setProperties(Map<Text, Text>) - Method in class org.apache.mahout.clustering.WeightedPropertyVectorWritable
 
setQ(int) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.SSVDSolver
sets q, amount of additional power iterations to increase precision (0..2!).
setQuick(int, int, double) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.UpperTriangular
 
setRadius(Vector) - Method in class org.apache.mahout.clustering.AbstractCluster
 
setRadius(Vector) - Method in class org.apache.mahout.clustering.dirichlet.models.GaussianCluster
 
setRecord(int) - Method in class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression
 
setRecord(int) - Method in class org.apache.mahout.classifier.sgd.CrossFoldLearner
 
setRow(int) - Method in class org.apache.mahout.clustering.spectral.common.VertexWritable
 
setRow(int) - Method in class org.apache.mahout.math.hadoop.DistributedRowMatrix.MatrixEntryWritable
 
setS0(double) - Method in class org.apache.mahout.clustering.AbstractCluster
 
setS1(Vector) - Method in class org.apache.mahout.clustering.AbstractCluster
 
setS2(Vector) - Method in class org.apache.mahout.clustering.AbstractCluster
 
setS3SafeCombinedInputPath(Job, Path, Path, Path) - Static method in class org.apache.mahout.common.AbstractJob
necessary to make this job (having a combined input path) work on Amazon S3, hopefully this is obsolete when MultipleInputs is available again
setScore(double) - Method in class org.apache.mahout.classifier.ClassifierResult
 
setSecond(int) - Method in class org.apache.mahout.common.IntPairWritable
 
setSeed(State<AdaptiveLogisticRegression.Wrapper, CrossFoldLearner>) - Method in class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression
 
setSequentialAccess(boolean) - Method in class org.apache.mahout.vectorizer.VectorizerConfig
 
setSerializations(Configuration) - Static method in class org.apache.mahout.common.HadoopUtil
 
setSigmaJSigmaK(double) - Method in class org.apache.mahout.classifier.bayes.InMemoryBayesDatastore
 
setSinglePath(boolean) - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.FPTree
 
setSkipCleanup(boolean) - Method in class org.apache.mahout.classifier.bayes.BayesParameters
 
setStep(double[]) - Method in class org.apache.mahout.ep.State
 
setStringValue(String) - Method in class org.apache.mahout.common.parameters.ClassParameter
 
setStringValue(String) - Method in class org.apache.mahout.common.parameters.CompositeParameter
 
setStringValue(String) - Method in class org.apache.mahout.common.parameters.DoubleParameter
 
setStringValue(String) - Method in class org.apache.mahout.common.parameters.FileParameter
 
setStringValue(String) - Method in class org.apache.mahout.common.parameters.IntegerParameter
 
setStringValue(String) - Method in interface org.apache.mahout.common.parameters.Parameter
 
setStringValue(String) - Method in class org.apache.mahout.common.parameters.PathParameter
 
setStringValue(String) - Method in class org.apache.mahout.common.parameters.StringParameter
 
setSum(double) - Method in class org.apache.mahout.math.hadoop.stats.VarianceTotals
 
setSumFeatureWeight(String, double) - Method in class org.apache.mahout.classifier.bayes.InMemoryBayesDatastore
 
setSumLabelWeight(String, double) - Method in class org.apache.mahout.classifier.bayes.InMemoryBayesDatastore
 
setSumOfSquares(double) - Method in class org.apache.mahout.math.hadoop.stats.VarianceTotals
 
setTaskItemOrdinal(long) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.SplitPartitionedWritable
 
setTempPrefs(PreferenceArray) - Method in class org.apache.mahout.cf.taste.impl.model.PlusAnonymousUserDataModel
 
setTfDirName(String) - Method in class org.apache.mahout.vectorizer.VectorizerConfig
 
setThetaNormalizer(String, double) - Method in class org.apache.mahout.classifier.bayes.InMemoryBayesDatastore
 
setThreadCount(int) - Method in class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression
 
setThreadCount(int) - Method in class org.apache.mahout.ep.EvolutionaryProcess
 
setTotalCount(double) - Method in class org.apache.mahout.math.hadoop.stats.VarianceTotals
 
setTraceDictionary(Map<String, Set<Integer>>) - Method in class org.apache.mahout.vectorizer.encoders.FeatureVectorEncoder
 
setType(String) - Method in class org.apache.mahout.clustering.spectral.common.VertexWritable
 
setup(Mapper<LongWritable, Text, DoubleWritable, NullWritable>.Context) - Method in class org.apache.mahout.cf.taste.hadoop.als.FactorizationEvaluator.PredictRatingsMapper
 
setup(Reducer<VarLongWritable, PrefAndSimilarityColumnWritable, VarLongWritable, RecommendedItemsWritable>.Context) - Method in class org.apache.mahout.cf.taste.hadoop.item.AggregateAndRecommendReducer
 
setup(Mapper<LongWritable, Text, VarIntWritable, VarLongWritable>.Context) - Method in class org.apache.mahout.cf.taste.hadoop.item.ItemIDIndexMapper
 
setup(Reducer<VarLongWritable, VarLongWritable, VarLongWritable, VectorWritable>.Context) - Method in class org.apache.mahout.cf.taste.hadoop.item.ToUserVectorsReducer
 
setup(Mapper<VarLongWritable, VectorWritable, VarIntWritable, VectorOrPrefWritable>.Context) - Method in class org.apache.mahout.cf.taste.hadoop.item.UserVectorSplitterMapper
 
setup(Mapper<VarLongWritable, VectorWritable, IntWritable, VectorWritable>.Context) - Method in class org.apache.mahout.cf.taste.hadoop.preparation.ToItemVectorsMapper
 
setup(Reducer<VarLongWritable, NullWritable, VarLongWritable, RecommendedItemsWritable>.Context) - Method in class org.apache.mahout.cf.taste.hadoop.pseudo.RecommenderReducer
 
setup(Mapper<IntWritable, VectorWritable, EntityEntityWritable, DoubleWritable>.Context) - Method in class org.apache.mahout.cf.taste.hadoop.similarity.item.ItemSimilarityJob.MostSimilarItemPairsMapper
 
setup(Mapper<LongWritable, Text, VarLongWritable, VarLongWritable>.Context) - Method in class org.apache.mahout.cf.taste.hadoop.ToEntityPrefsMapper
 
setup(Mapper<LongWritable, Text, DoubleWritable, Text>.Context) - Method in class org.apache.mahout.classifier.df.mapreduce.Classifier.CMapper
 
setup(Mapper<IntWritable, NullWritable, IntWritable, MapredOutput>.Context) - Method in class org.apache.mahout.classifier.df.mapreduce.inmem.InMemMapper
 
setup(Mapper<KEYIN, VALUEIN, KEYOUT, VALUEOUT>.Context) - Method in class org.apache.mahout.classifier.df.mapreduce.MapredMapper
 
setup(Mapper<LongWritable, Text, TreeID, MapredOutput>.Context) - Method in class org.apache.mahout.classifier.df.mapreduce.partial.Step1Mapper
 
setup(Mapper<Text, VectorWritable, Text, VectorWritable>.Context) - Method in class org.apache.mahout.classifier.naivebayes.test.BayesTestMapper
 
setup(Mapper<Text, VectorWritable, IntWritable, VectorWritable>.Context) - Method in class org.apache.mahout.classifier.naivebayes.training.IndexInstancesMapper
 
setup(Mapper<IntWritable, VectorWritable, Text, VectorWritable>.Context) - Method in class org.apache.mahout.classifier.naivebayes.training.ThetaMapper
 
setup(Mapper<IntWritable, VectorWritable, Text, VectorWritable>.Context) - Method in class org.apache.mahout.classifier.naivebayes.training.WeightsMapper
 
setup(Reducer<Text, VectorWritable, Text, Canopy>.Context) - Method in class org.apache.mahout.clustering.canopy.CanopyReducer
 
setup(Mapper<WritableComparable<?>, VectorWritable, IntWritable, WeightedVectorWritable>.Context) - Method in class org.apache.mahout.clustering.canopy.ClusterMapper
 
setup(Mapper<WritableComparable<?>, VectorWritable, IntWritable, Cluster>.Context) - Method in class org.apache.mahout.clustering.CIMapper
 
setup(Mapper<WritableComparable<?>, VectorWritable, IntWritable, WeightedVectorWritable>.Context) - Method in class org.apache.mahout.clustering.dirichlet.DirichletClusterMapper
 
setup(Mapper<WritableComparable<?>, VectorWritable, Text, VectorWritable>.Context) - Method in class org.apache.mahout.clustering.dirichlet.DirichletMapper
 
setup(DirichletState) - Method in class org.apache.mahout.clustering.dirichlet.DirichletMapper
 
setup(Reducer<Text, VectorWritable, Text, DirichletCluster>.Context) - Method in class org.apache.mahout.clustering.dirichlet.DirichletReducer
 
setup(DirichletState) - Method in class org.apache.mahout.clustering.dirichlet.DirichletReducer
 
setup(Mapper<WritableComparable<?>, VectorWritable, IntWritable, WeightedVectorWritable>.Context) - Method in class org.apache.mahout.clustering.fuzzykmeans.FuzzyKMeansClusterMapper
 
setup(Reducer<Text, ClusterObservations, Text, ClusterObservations>.Context) - Method in class org.apache.mahout.clustering.fuzzykmeans.FuzzyKMeansCombiner
 
setup(Mapper<WritableComparable<?>, VectorWritable, Text, ClusterObservations>.Context) - Method in class org.apache.mahout.clustering.fuzzykmeans.FuzzyKMeansMapper
 
setup(Reducer<Text, ClusterObservations, Text, SoftCluster>.Context) - Method in class org.apache.mahout.clustering.fuzzykmeans.FuzzyKMeansReducer
 
setup(Collection<SoftCluster>, Configuration) - Method in class org.apache.mahout.clustering.fuzzykmeans.FuzzyKMeansReducer
 
setup(Mapper<WritableComparable<?>, VectorWritable, IntWritable, WeightedPropertyVectorWritable>.Context) - Method in class org.apache.mahout.clustering.kmeans.KMeansClusterMapper
 
setup(Mapper<WritableComparable<?>, VectorWritable, Text, ClusterObservations>.Context) - Method in class org.apache.mahout.clustering.kmeans.KMeansMapper
 
setup(Reducer<Text, ClusterObservations, Text, Cluster>.Context) - Method in class org.apache.mahout.clustering.kmeans.KMeansReducer
 
setup(Collection<Cluster>, DistanceMeasure) - Method in class org.apache.mahout.clustering.kmeans.KMeansReducer
 
setup(Mapper<IntWritable, VectorWritable, IntWritable, VectorWritable>.Context) - Method in class org.apache.mahout.clustering.lda.cvb.CachingCVB0Mapper
 
setup(Mapper<IntWritable, VectorWritable, DoubleWritable, DoubleWritable>.Context) - Method in class org.apache.mahout.clustering.lda.cvb.CachingCVB0PerplexityMapper
 
setup(Mapper<WritableComparable<?>, VectorWritable, WritableComparable<?>, VectorWritable>.Context) - Method in class org.apache.mahout.clustering.lda.LDADocumentTopicMapper
 
setup(Mapper<WritableComparable<?>, VectorWritable, IntPairWritable, DoubleWritable>.Context) - Method in class org.apache.mahout.clustering.lda.LDAWordTopicMapper
 
setup(Mapper<WritableComparable<?>, MeanShiftCanopy, IntWritable, WeightedVectorWritable>.Context) - Method in class org.apache.mahout.clustering.meanshift.MeanShiftCanopyClusterMapper
 
setup(Mapper<WritableComparable<?>, VectorWritable, Text, MeanShiftCanopy>.Context) - Method in class org.apache.mahout.clustering.meanshift.MeanShiftCanopyCreatorMapper
 
setup(Mapper<WritableComparable<?>, MeanShiftCanopy, Text, MeanShiftCanopy>.Context) - Method in class org.apache.mahout.clustering.meanshift.MeanShiftCanopyMapper
 
setup(Reducer<Text, MeanShiftCanopy, Text, MeanShiftCanopy>.Context) - Method in class org.apache.mahout.clustering.meanshift.MeanShiftCanopyReducer
 
setup(Mapper<Text, VectorWritable, Text, Writable>.Context) - Method in class org.apache.mahout.clustering.minhash.MinHashMapper
 
setup(Reducer<Text, Writable, Text, Writable>.Context) - Method in class org.apache.mahout.clustering.minhash.MinHashReducer
 
setup(Mapper<IntWritable, VectorWritable, IntWritable, VectorWritable>.Context) - Method in class org.apache.mahout.clustering.spectral.common.VectorMatrixMultiplicationJob.VectorMatrixMultiplicationMapper
 
setup(Mapper<IntWritable, VectorWritable, IntWritable, EigencutsSensitivityNode>.Context) - Method in class org.apache.mahout.clustering.spectral.eigencuts.EigencutsSensitivityMapper
 
setup(Reducer<Text, TopKStringPatterns, Text, TopKStringPatterns>.Context) - Method in class org.apache.mahout.fpm.pfpgrowth.AggregatorReducer
 
setup(Mapper<LongWritable, Text, Text, LongWritable>.Context) - Method in class org.apache.mahout.fpm.pfpgrowth.ParallelCountingMapper
 
setup(Mapper<LongWritable, Text, IntWritable, TransactionTree>.Context) - Method in class org.apache.mahout.fpm.pfpgrowth.ParallelFPGrowthMapper
 
setup(Reducer<IntWritable, TransactionTree, Text, TopKStringPatterns>.Context) - Method in class org.apache.mahout.fpm.pfpgrowth.ParallelFPGrowthReducer
 
setup(Mapper<LongWritable, Text, LongWritable, DoubleWritable>.Context) - Method in class org.apache.mahout.ga.watchmaker.EvalMapper
 
setup(Mapper<IntWritable, VectorWritable, IntWritable, VectorWritable>.Context) - Method in class org.apache.mahout.math.hadoop.similarity.cooccurrence.RowSimilarityJob.CooccurrencesMapper
 
setup(Reducer<IntWritable, VectorWritable, IntWritable, VectorWritable>.Context) - Method in class org.apache.mahout.math.hadoop.similarity.cooccurrence.RowSimilarityJob.MergeToTopKSimilaritiesReducer
 
setup(Reducer<IntWritable, VectorWritable, IntWritable, VectorWritable>.Context) - Method in class org.apache.mahout.math.hadoop.similarity.cooccurrence.RowSimilarityJob.MergeVectorsReducer
 
setup(Reducer<IntWritable, VectorWritable, IntWritable, VectorWritable>.Context) - Method in class org.apache.mahout.math.hadoop.similarity.cooccurrence.RowSimilarityJob.SimilarityReducer
 
setup(Mapper.Context) - Method in class org.apache.mahout.math.hadoop.similarity.cooccurrence.RowSimilarityJob.UnsymmetrifyMapper
 
setup(Mapper<IntWritable, VectorWritable, IntWritable, VectorWritable>.Context) - Method in class org.apache.mahout.math.hadoop.similarity.cooccurrence.RowSimilarityJob.VectorNormMapper
 
setup(Mapper<WritableComparable<?>, VectorWritable, Text, VectorWritable>.Context) - Method in class org.apache.mahout.math.hadoop.similarity.VectorDistanceInvertedMapper
 
setup(Mapper<WritableComparable<?>, VectorWritable, StringTuple, DoubleWritable>.Context) - Method in class org.apache.mahout.math.hadoop.similarity.VectorDistanceMapper
 
setup(Mapper<Writable, VectorWritable, SplitPartitionedWritable, DenseBlockWritable>.Context) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.ABtDenseOutJob.ABtMapper
 
setup(Reducer<SplitPartitionedWritable, DenseBlockWritable, SplitPartitionedWritable, VectorWritable>.Context) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.ABtDenseOutJob.QRReducer
 
setup(Mapper<Writable, VectorWritable, SplitPartitionedWritable, SparseRowBlockWritable>.Context) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.ABtJob.ABtMapper
 
setup(Reducer<SplitPartitionedWritable, SparseRowBlockWritable, SplitPartitionedWritable, VectorWritable>.Context) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.ABtJob.QRReducer
 
setup(Mapper<Writable, VectorWritable, LongWritable, SparseRowBlockWritable>.Context) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.BtJob.BtMapper
 
setup(Reducer<Writable, SparseRowBlockWritable, Writable, SparseRowBlockWritable>.Context) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.BtJob.OuterProductCombiner
 
setup(Reducer<LongWritable, SparseRowBlockWritable, IntWritable, VectorWritable>.Context) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.BtJob.OuterProductReducer
 
setup(Mapper<Writable, VectorWritable, SplitPartitionedWritable, VectorWritable>.Context) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.QJob.QMapper
 
setup() - Method in class org.apache.mahout.math.hadoop.stochasticsvd.qr.QRFirstStep
 
setup(Mapper<Writable, VectorWritable, Writable, VectorWritable>.Context) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.UJob.UMapper
 
setup(Mapper<IntWritable, VectorWritable, IntWritable, VectorWritable>.Context) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.VJob.VMapper
 
setup(Mapper<Writable, VectorWritable, IntWritable, VectorWritable>.Context) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.YtYJob.YtYMapper
 
setup(Reducer<IntWritable, VectorWritable, IntWritable, VectorWritable>.Context) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.YtYJob.YtYReducer
 
setup(Reducer<NullWritable, DoubleWritable, NullWritable, DoubleWritable>.Context) - Method in class org.apache.mahout.math.stats.entropy.CalculateEntropyReducer
 
setup(Reducer<Text, VarIntWritable, Text, DoubleWritable>.Context) - Method in class org.apache.mahout.math.stats.entropy.SpecificConditionalEntropyReducer
 
setup(Mapper<Text, StringTuple, GramKey, Gram>.Context) - Method in class org.apache.mahout.vectorizer.collocations.llr.CollocMapper
 
setup(Reducer<GramKey, Gram, Gram, Gram>.Context) - Method in class org.apache.mahout.vectorizer.collocations.llr.CollocReducer
 
setup(Reducer<Gram, Gram, Text, DoubleWritable>.Context) - Method in class org.apache.mahout.vectorizer.collocations.llr.LLRReducer
 
setup(Reducer<WritableComparable<?>, VectorWritable, WritableComparable<?>, VectorWritable>.Context) - Method in class org.apache.mahout.vectorizer.common.PartialVectorMergeReducer
 
setup(Mapper<Text, Text, Text, StringTuple>.Context) - Method in class org.apache.mahout.vectorizer.document.SequenceFileTokenizerMapper
 
setup(Mapper<Text, Text, Text, VectorWritable>.Context) - Method in class org.apache.mahout.vectorizer.EncodingMapper
 
setup(Reducer<WritableComparable<?>, VectorWritable, WritableComparable<?>, VectorWritable>.Context) - Method in class org.apache.mahout.vectorizer.pruner.PrunedPartialVectorMergeReducer
 
setup(Reducer<WritableComparable<?>, VectorWritable, WritableComparable<?>, VectorWritable>.Context) - Method in class org.apache.mahout.vectorizer.pruner.WordsPrunerReducer
 
setup(Reducer<Text, LongWritable, Text, LongWritable>.Context) - Method in class org.apache.mahout.vectorizer.term.TermCountReducer
 
setup(Reducer<Text, StringTuple, Text, VectorWritable>.Context) - Method in class org.apache.mahout.vectorizer.term.TFPartialVectorReducer
 
setup(Reducer<WritableComparable<?>, VectorWritable, WritableComparable<?>, VectorWritable>.Context) - Method in class org.apache.mahout.vectorizer.tfidf.TFIDFPartialVectorReducer
 
setupBlock(Reducer<SplitPartitionedWritable, DenseBlockWritable, SplitPartitionedWritable, VectorWritable>.Context, SplitPartitionedWritable) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.ABtDenseOutJob.QRReducer
 
setupBlock(Reducer<SplitPartitionedWritable, SparseRowBlockWritable, SplitPartitionedWritable, VectorWritable>.Context, SplitPartitionedWritable) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.ABtJob.QRReducer
 
setUserID(int, long) - Method in class org.apache.mahout.cf.taste.impl.model.BooleanItemPreferenceArray
 
setUserID(int, long) - Method in class org.apache.mahout.cf.taste.impl.model.BooleanUserPreferenceArray
Sets user ID for preference at i.
setUserID(int, long) - Method in class org.apache.mahout.cf.taste.impl.model.GenericItemPreferenceArray
 
setUserID(int, long) - Method in class org.apache.mahout.cf.taste.impl.model.GenericUserPreferenceArray
Sets user ID for preference at i.
setUserID(int, long) - Method in interface org.apache.mahout.cf.taste.model.PreferenceArray
Sets user ID for preference at i.
setVal(double) - Method in class org.apache.mahout.math.hadoop.DistributedRowMatrix.MatrixEntryWritable
 
setValue(int, float) - Method in class org.apache.mahout.cf.taste.impl.model.BooleanItemPreferenceArray
 
setValue(float) - Method in class org.apache.mahout.cf.taste.impl.model.BooleanPreference
 
setValue(int, float) - Method in class org.apache.mahout.cf.taste.impl.model.BooleanUserPreferenceArray
 
setValue(int, float) - Method in class org.apache.mahout.cf.taste.impl.model.GenericItemPreferenceArray
 
setValue(float) - Method in class org.apache.mahout.cf.taste.impl.model.GenericPreference
 
setValue(int, float) - Method in class org.apache.mahout.cf.taste.impl.model.GenericUserPreferenceArray
 
setValue(float) - Method in interface org.apache.mahout.cf.taste.model.Preference
Sets the strength of the preference for this item
setValue(int, float) - Method in interface org.apache.mahout.cf.taste.model.PreferenceArray
Sets preference value for preference at i.
setValue(double) - Method in class org.apache.mahout.clustering.spectral.common.IntDoublePairWritable
 
setValue(double) - Method in class org.apache.mahout.clustering.spectral.common.VertexWritable
 
setValue(double) - Method in class org.apache.mahout.ep.State
 
setVector(Vector) - Method in class org.apache.mahout.clustering.WeightedVectorWritable
 
setVector(Vector) - Method in class org.apache.mahout.math.MultiLabelVectorWritable
 
setVerbose(boolean) - Method in class org.apache.mahout.clustering.lda.cvb.InMemoryCollapsedVariationalBayes0
 
setWeights(Vector) - Method in class org.apache.mahout.common.distance.WeightedDistanceMeasure
 
setWindowSize(int) - Method in class org.apache.mahout.classifier.sgd.CrossFoldLearner
 
setWindowSize(int) - Method in class org.apache.mahout.math.stats.GlobalOnlineAuc
 
setWindowSize(int) - Method in class org.apache.mahout.math.stats.GroupedOnlineAuc
 
setWindowSize(int) - Method in interface org.apache.mahout.math.stats.OnlineAuc
 
setWordEncoder(FeatureVectorEncoder) - Method in class org.apache.mahout.vectorizer.encoders.TextValueEncoder
 
setWritesLaxPrecision(boolean) - Method in class org.apache.mahout.math.VectorWritable
 
shallowCopy() - Method in class org.apache.mahout.clustering.meanshift.MeanShiftCanopy
 
shiftBias(double) - Method in class org.apache.mahout.classifier.discriminative.LinearModel
Shift the bias of the model.
shiftToMean(MeanShiftCanopy) - Method in class org.apache.mahout.clustering.meanshift.MeanShiftCanopyClusterer
Shift the center to the new centroid of the cluster
shouldRunNextPhase(Map<String, String>, AtomicInteger) - Static method in class org.apache.mahout.common.AbstractJob
 
similarity(double, double, double, int) - Method in class org.apache.mahout.math.hadoop.similarity.cooccurrence.measures.CityBlockSimilarity
 
similarity(double, double, double, int) - Method in class org.apache.mahout.math.hadoop.similarity.cooccurrence.measures.CooccurrenceCountSimilarity
 
similarity(double, double, double, int) - Method in class org.apache.mahout.math.hadoop.similarity.cooccurrence.measures.CosineSimilarity
 
similarity(double, double, double, int) - Method in class org.apache.mahout.math.hadoop.similarity.cooccurrence.measures.EuclideanDistanceSimilarity
 
similarity(double, double, double, int) - Method in class org.apache.mahout.math.hadoop.similarity.cooccurrence.measures.LoglikelihoodSimilarity
 
similarity(double, double, double, int) - Method in class org.apache.mahout.math.hadoop.similarity.cooccurrence.measures.TanimotoCoefficientSimilarity
 
similarity(double, double, double, int) - Method in interface org.apache.mahout.math.hadoop.similarity.cooccurrence.measures.VectorSimilarityMeasure
 
SimilarityMatrixRowWrapperMapper - Class in org.apache.mahout.cf.taste.hadoop.item
maps a row of the similarity matrix to a VectorOrPrefWritable actually a column from that matrix has to be used but as the similarity matrix is symmetric, we can use a row instead of having to transpose it
SimilarityMatrixRowWrapperMapper() - Constructor for class org.apache.mahout.cf.taste.hadoop.item.SimilarityMatrixRowWrapperMapper
 
SimilarityTransform - Interface in org.apache.mahout.cf.taste.transforms
Implementations encapsulate some transformation on similarity values between two things, where things might be IDs of users or items or something else.
SimilarUser - Class in org.apache.mahout.cf.taste.impl.recommender
Simply encapsulates a user and a similarity value.
SimilarUser(long, double) - Constructor for class org.apache.mahout.cf.taste.impl.recommender.SimilarUser
 
SimpleTextEncodingVectorizer - Class in org.apache.mahout.vectorizer
Runs a Map/Reduce job that encodes FeatureVectorEncoder the input and writes it to the output as a sequence file.
SimpleTextEncodingVectorizer() - Constructor for class org.apache.mahout.vectorizer.SimpleTextEncodingVectorizer
 
singlePath() - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.FPTree
 
SINGULAR_PREFIX - Static variable in class org.apache.mahout.math.hadoop.decomposer.HdfsBackedLanczosState
 
size() - Method in class org.apache.mahout.cf.taste.impl.common.FastByIDMap
 
size() - Method in class org.apache.mahout.cf.taste.impl.common.FastIDSet
 
size() - Method in class org.apache.mahout.cf.taste.impl.common.FastMap
 
size() - Method in class org.apache.mahout.classifier.df.data.Data
 
size() - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.LeastKCache
 
size() - Method in class org.apache.mahout.vectorizer.encoders.Dictionary
 
skip(int) - Method in class org.apache.mahout.cf.taste.impl.common.jdbc.ResultSetIterator
 
skip(int) - Method in class org.apache.mahout.cf.taste.impl.common.LongPrimitiveArrayIterator
 
skip(int) - Method in class org.apache.mahout.cf.taste.impl.common.SamplingLongPrimitiveIterator
 
skip(int) - Method in interface org.apache.mahout.cf.taste.impl.common.SkippingIterator
Skip the next n elements supplied by this Iterator.
skip(int) - Method in class org.apache.mahout.common.iterator.FileLineIterator
 
SkippingIterator<V> - Interface in org.apache.mahout.cf.taste.impl.common
Adds ability to skip ahead in an iterator, perhaps more efficiently than by calling Iterator.next() repeatedly.
SlopeOneAverageDiffsJob - Class in org.apache.mahout.cf.taste.hadoop.slopeone
 
SlopeOneAverageDiffsJob() - Constructor for class org.apache.mahout.cf.taste.hadoop.slopeone.SlopeOneAverageDiffsJob
 
SlopeOneDiffsToAveragesReducer - Class in org.apache.mahout.cf.taste.hadoop.slopeone
 
SlopeOneDiffsToAveragesReducer() - Constructor for class org.apache.mahout.cf.taste.hadoop.slopeone.SlopeOneDiffsToAveragesReducer
 
SlopeOnePrefsToDiffsReducer - Class in org.apache.mahout.cf.taste.hadoop.slopeone
 
SlopeOnePrefsToDiffsReducer() - Constructor for class org.apache.mahout.cf.taste.hadoop.slopeone.SlopeOnePrefsToDiffsReducer
 
SlopeOneRecommender - Class in org.apache.mahout.cf.taste.impl.recommender.slopeone
A basic "slope one" recommender.
SlopeOneRecommender(DataModel) - Constructor for class org.apache.mahout.cf.taste.impl.recommender.slopeone.SlopeOneRecommender
Creates a default (weighted) based on the given DataModel.
SlopeOneRecommender(DataModel, Weighting, Weighting, DiffStorage) - Constructor for class org.apache.mahout.cf.taste.impl.recommender.slopeone.SlopeOneRecommender
Creates a based on the given DataModel.
smallestGreat() - Method in class org.apache.mahout.cf.taste.common.TopK
 
SoftCluster - Class in org.apache.mahout.clustering.fuzzykmeans
 
SoftCluster() - Constructor for class org.apache.mahout.clustering.fuzzykmeans.SoftCluster
 
SoftCluster(Vector, int, DistanceMeasure) - Constructor for class org.apache.mahout.clustering.fuzzykmeans.SoftCluster
Construct a new SoftCluster with the given point as its center
softLimit(double, double, double) - Static method in class org.apache.mahout.ep.Mapping
Maps input to the open interval (min, max) with 0 going to the mean of min and max.
softLimit(double, double) - Static method in class org.apache.mahout.ep.Mapping
Maps input to the open interval (min, max) with 0 going to the mean of min and max.
solve(Matrix) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.qr.GivensThinSolver
 
sortByItem() - Method in class org.apache.mahout.cf.taste.impl.model.BooleanItemPreferenceArray
 
sortByItem() - Method in class org.apache.mahout.cf.taste.impl.model.BooleanUserPreferenceArray
 
sortByItem() - Method in class org.apache.mahout.cf.taste.impl.model.GenericItemPreferenceArray
 
sortByItem() - Method in class org.apache.mahout.cf.taste.impl.model.GenericUserPreferenceArray
 
sortByItem() - Method in interface org.apache.mahout.cf.taste.model.PreferenceArray
Sorts underlying array by item ID, ascending.
sortByUser() - Method in class org.apache.mahout.cf.taste.impl.model.BooleanItemPreferenceArray
 
sortByUser() - Method in class org.apache.mahout.cf.taste.impl.model.BooleanUserPreferenceArray
 
sortByUser() - Method in class org.apache.mahout.cf.taste.impl.model.GenericItemPreferenceArray
 
sortByUser() - Method in class org.apache.mahout.cf.taste.impl.model.GenericUserPreferenceArray
 
sortByUser() - Method in interface org.apache.mahout.cf.taste.model.PreferenceArray
Sorts underlying array by user ID, ascending.
sortByValue() - Method in class org.apache.mahout.cf.taste.impl.model.BooleanItemPreferenceArray
 
sortByValue() - Method in class org.apache.mahout.cf.taste.impl.model.BooleanUserPreferenceArray
 
sortByValue() - Method in class org.apache.mahout.cf.taste.impl.model.GenericItemPreferenceArray
 
sortByValue() - Method in class org.apache.mahout.cf.taste.impl.model.GenericUserPreferenceArray
 
sortByValue() - Method in interface org.apache.mahout.cf.taste.model.PreferenceArray
Sorts underlying array by preference value, ascending.
sortByValueReversed() - Method in class org.apache.mahout.cf.taste.impl.model.BooleanItemPreferenceArray
 
sortByValueReversed() - Method in class org.apache.mahout.cf.taste.impl.model.BooleanUserPreferenceArray
 
sortByValueReversed() - Method in class org.apache.mahout.cf.taste.impl.model.GenericItemPreferenceArray
 
sortByValueReversed() - Method in class org.apache.mahout.cf.taste.impl.model.GenericUserPreferenceArray
 
sortByValueReversed() - Method in interface org.apache.mahout.cf.taste.model.PreferenceArray
Sorts underlying array by preference value, descending.
sortingComparator(Comparator<? super T>) - Method in class org.apache.mahout.cf.taste.common.MinK
 
sortingComparator(Comparator<? super T>) - Method in class org.apache.mahout.cf.taste.common.TopK
 
sortSplits(InputSplit[]) - Static method in class org.apache.mahout.classifier.df.mapreduce.Builder
sort the splits into order based on size, so that the biggest go first.
This is the same code used by Hadoop's JobClient.
SparseRowBlockAccumulator - Class in org.apache.mahout.math.hadoop.stochasticsvd
Aggregate incoming rows into blocks based on the row number (long).
SparseRowBlockAccumulator(int, OutputCollector<LongWritable, SparseRowBlockWritable>) - Constructor for class org.apache.mahout.math.hadoop.stochasticsvd.SparseRowBlockAccumulator
 
SparseRowBlockWritable - Class in org.apache.mahout.math.hadoop.stochasticsvd
block that supports accumulating rows and their sums , suitable for combiner and reducers of multiplication jobs.
SparseRowBlockWritable() - Constructor for class org.apache.mahout.math.hadoop.stochasticsvd.SparseRowBlockWritable
 
SparseRowBlockWritable(int) - Constructor for class org.apache.mahout.math.hadoop.stochasticsvd.SparseRowBlockWritable
 
SparseVectorsFromSequenceFiles - Class in org.apache.mahout.vectorizer
Converts a given set of sequence files into SparseVectors
SparseVectorsFromSequenceFiles() - Constructor for class org.apache.mahout.vectorizer.SparseVectorsFromSequenceFiles
 
sparsity(double) - Method in class org.apache.mahout.classifier.sgd.GradientMachine
Chainable configuration option.
sparsityLearningRate(double) - Method in class org.apache.mahout.classifier.sgd.GradientMachine
Chainable configuration option.
SpearmanCorrelationSimilarity - Class in org.apache.mahout.cf.taste.impl.similarity
Like PearsonCorrelationSimilarity, but compares relative ranking of preference values instead of preference values themselves.
SpearmanCorrelationSimilarity(DataModel) - Constructor for class org.apache.mahout.cf.taste.impl.similarity.SpearmanCorrelationSimilarity
 
SpecificConditionalEntropyMapper - Class in org.apache.mahout.math.stats.entropy
Converts the key from StringTuple with values [key, value] to Text with value key.
SpecificConditionalEntropyMapper() - Constructor for class org.apache.mahout.math.stats.entropy.SpecificConditionalEntropyMapper
 
SpecificConditionalEntropyReducer - Class in org.apache.mahout.math.stats.entropy
Does the weighted conditional entropy calculation with

H(values|key) = p(key) * sum_i(p(values_i|key) * log_2(p(values_i|key))) = p(key) * (log(|key|) - sum_i(values_i * log_2(values_i)) / |key|) = (sum * log_2(sum) - sum_i(values_i * log_2(values_i))/n WITH sum = sum_i(values_i) = (sum * log(sum) - sum_i(values_i * log(values_i)) / (n * log(2))

SpecificConditionalEntropyReducer() - Constructor for class org.apache.mahout.math.stats.entropy.SpecificConditionalEntropyReducer
 
SpectralKMeansDriver - Class in org.apache.mahout.clustering.spectral.kmeans
Implementation of the EigenCuts spectral clustering algorithm.
SpectralKMeansDriver() - Constructor for class org.apache.mahout.clustering.spectral.kmeans.SpectralKMeansDriver
 
Split - Class in org.apache.mahout.classifier.df.split
Contains enough information to identify each split
Split(int, double, double) - Constructor for class org.apache.mahout.classifier.df.split.Split
 
Split(int, double) - Constructor for class org.apache.mahout.classifier.df.split.Split
 
SPLIT_PATTERN - Static variable in class org.apache.mahout.fpm.pfpgrowth.PFPGrowth
 
SplitPartitionedWritable - Class in org.apache.mahout.math.hadoop.stochasticsvd
a key for vectors allowing to identify them by their coordinates in original split of A.
SplitPartitionedWritable(Mapper<?, ?, ?, ?>.Context) - Constructor for class org.apache.mahout.math.hadoop.stochasticsvd.SplitPartitionedWritable
 
SplitPartitionedWritable() - Constructor for class org.apache.mahout.math.hadoop.stochasticsvd.SplitPartitionedWritable
 
SplitPartitionedWritable.SplitGroupingComparator - Class in org.apache.mahout.math.hadoop.stochasticsvd
 
SplitPartitionedWritable.SplitGroupingComparator() - Constructor for class org.apache.mahout.math.hadoop.stochasticsvd.SplitPartitionedWritable.SplitGroupingComparator
 
splitPrefTokens(CharSequence) - Static method in class org.apache.mahout.cf.taste.hadoop.TasteHadoopUtils
Splits a preference data line into string tokens
splitSinglePrefix() - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth2.FPTree
Return a pair of trees that result from separating a common prefix (if one exists) from the lower portion of this tree.
SPLITTER - Static variable in class org.apache.mahout.fpm.pfpgrowth.PFPGrowth
 
SQRT2PI - Static variable in class org.apache.mahout.clustering.dirichlet.UncommonDistributions
 
SquaredEuclideanDistanceMeasure - Class in org.apache.mahout.common.distance
Like EuclideanDistanceMeasure but it does not take the square root.
SquaredEuclideanDistanceMeasure() - Constructor for class org.apache.mahout.common.distance.SquaredEuclideanDistanceMeasure
 
SSVDCli - Class in org.apache.mahout.math.hadoop.stochasticsvd
Mahout CLI adapter for SSVDSolver
SSVDCli() - Constructor for class org.apache.mahout.math.hadoop.stochasticsvd.SSVDCli
 
SSVDPrototype - Class in org.apache.mahout.math.hadoop.stochasticsvd
SSVD protoptype: non-MR concept verification for Givens QR & SSVD basic algorithms
SSVDPrototype(long, int, int) - Constructor for class org.apache.mahout.math.hadoop.stochasticsvd.SSVDPrototype
 
SSVDSolver - Class in org.apache.mahout.math.hadoop.stochasticsvd
Stochastic SVD solver (API class).
SSVDSolver(Configuration, Path[], Path, int, int, int, int) - Constructor for class org.apache.mahout.math.hadoop.stochasticsvd.SSVDSolver
create new SSVD solver.
StableFixedSizeSamplingIterator<T> - Class in org.apache.mahout.common.iterator
Sample a fixed number of elements from an Iterator.
StableFixedSizeSamplingIterator(int, Iterator<T>) - Constructor for class org.apache.mahout.common.iterator.StableFixedSizeSamplingIterator
 
stage1OutputPath(Path, int) - Static method in class org.apache.mahout.clustering.lda.cvb.CVB0Driver
 
StandardDeviationCalculatorMapper - Class in org.apache.mahout.math.hadoop.stats
 
StandardDeviationCalculatorMapper() - Constructor for class org.apache.mahout.math.hadoop.stats.StandardDeviationCalculatorMapper
 
StandardDeviationCalculatorReducer - Class in org.apache.mahout.math.hadoop.stats
 
StandardDeviationCalculatorReducer() - Constructor for class org.apache.mahout.math.hadoop.stats.StandardDeviationCalculatorReducer
 
StandardNaiveBayesClassifier - Class in org.apache.mahout.classifier.naivebayes
Class implementing the Naive Bayes Classifier Algorithm
StandardNaiveBayesClassifier(NaiveBayesModel) - Constructor for class org.apache.mahout.classifier.naivebayes.StandardNaiveBayesClassifier
 
StandardThetaTrainer - Class in org.apache.mahout.classifier.naivebayes.training
 
StandardThetaTrainer(Vector, Vector, double) - Constructor for class org.apache.mahout.classifier.naivebayes.training.StandardThetaTrainer
 
start() - Method in class org.apache.mahout.clustering.lda.cvb.ModelTrainer
 
start(Configuration, Path, Path, Path, Path, int, int, Class<? extends Writable>, boolean) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.UJob
 
start(Configuration, Path, Path, Path, Path, int, int, boolean) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.VJob
 
startAggregating(Parameters, Configuration) - Static method in class org.apache.mahout.fpm.pfpgrowth.PFPGrowth
Run the aggregation Job to aggregate the different TopK patterns and group each Pattern by the features present in it and thus calculate the final Top K frequent Patterns for each feature
startMemoryLogger(long) - Static method in class org.apache.mahout.common.MemoryUtil
Constructs and starts a memory logger thread.
startMemoryLogger() - Static method in class org.apache.mahout.common.MemoryUtil
Constructs and starts a memory logger thread with a logging rate of 1000 milliseconds.
startParallelCounting(Parameters, Configuration) - Static method in class org.apache.mahout.fpm.pfpgrowth.PFPGrowth
Count the frequencies of various features in parallel using Map/Reduce
startParallelFPGrowth(Parameters, Configuration) - Static method in class org.apache.mahout.fpm.pfpgrowth.PFPGrowth
Run the Parallel FPGrowth Map/Reduce Job to calculate the Top K features of group dependent shards
State<T extends Payload<U>,U> - Class in org.apache.mahout.ep
Records evolutionary state and provides a mutation operation for recorded-step meta-mutation.
State() - Constructor for class org.apache.mahout.ep.State
 
State(double[], double) - Constructor for class org.apache.mahout.ep.State
Invent a new state with no momentum (yet).
STATE_IN_KEY - Static variable in class org.apache.mahout.clustering.dirichlet.DirichletDriver
 
STATE_IN_KEY - Static variable in class org.apache.mahout.clustering.meanshift.MeanShiftCanopyDriver
 
StaticWordValueEncoder - Class in org.apache.mahout.vectorizer.encoders
Encodes a categorical values with an unbounded vocabulary.
StaticWordValueEncoder(String) - Constructor for class org.apache.mahout.vectorizer.encoders.StaticWordValueEncoder
 
StatusUpdater - Interface in org.apache.mahout.fpm.pfpgrowth.convertors
An interface of a Status updater
STD_CALC_DIR - Static variable in class org.apache.mahout.vectorizer.HighDFWordsPruner
 
stdDev(Path, Path, Configuration) - Static method in class org.apache.mahout.math.hadoop.stats.BasicStats
Calculate the standard deviation
stdDevForGivenMean(Path, Path, double, Configuration) - Static method in class org.apache.mahout.math.hadoop.stats.BasicStats
Calculate the standard deviation given a predefined mean
step - Variable in class org.apache.mahout.classifier.sgd.AbstractOnlineLogisticRegression
 
Step1Mapper - Class in org.apache.mahout.classifier.df.mapreduce.partial
First step of the Partial Data Builder.
Step1Mapper() - Constructor for class org.apache.mahout.classifier.df.mapreduce.partial.Step1Mapper
 
stepOffset(int) - Method in class org.apache.mahout.classifier.sgd.CrossFoldLearner
 
stepOffset(int) - Method in class org.apache.mahout.classifier.sgd.OnlineLogisticRegression
 
stepSize(int, double) - Static method in class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression
 
STEvolutionEngine<T> - Class in org.apache.mahout.ga.watchmaker
Single Threaded Evolution Engine.
STEvolutionEngine(CandidateFactory<T>, EvolutionaryOperator<T>, FitnessEvaluator<? super T>, SelectionStrategy<? super T>, Random) - Constructor for class org.apache.mahout.ga.watchmaker.STEvolutionEngine
 
STFitnessEvaluator<T> - Class in org.apache.mahout.ga.watchmaker
Special Fitness Evaluator that evaluates all the population ones.
STFitnessEvaluator() - Constructor for class org.apache.mahout.ga.watchmaker.STFitnessEvaluator
 
stop() - Method in class org.apache.mahout.clustering.lda.cvb.ModelTrainer
 
stopMemoryLogger() - Static method in class org.apache.mahout.common.MemoryUtil
Stops the memory logger, if any, started via MemoryUtil.startMemoryLogger(long) or MemoryUtil.startMemoryLogger().
storeMapping(long, String) - Method in class org.apache.mahout.cf.taste.impl.model.AbstractJDBCIDMigrator
 
storeMapping(long, String) - Method in class org.apache.mahout.cf.taste.impl.model.MemoryIDMigrator
 
storeMapping(long, String) - Method in interface org.apache.mahout.cf.taste.model.UpdatableIDMigrator
Stores the reverse long-to-String mapping in some kind of backing store.
storeWritable(Configuration, Path, Writable) - Static method in class org.apache.mahout.classifier.df.DFUtils
 
stringAt(int) - Method in class org.apache.mahout.common.StringTuple
Fetches the string at the given location
StringOutputConverter - Class in org.apache.mahout.fpm.pfpgrowth.convertors.string
Collects a string pattern in a MaxHeap and outputs the top K patterns
StringOutputConverter(OutputCollector<Text, TopKStringPatterns>) - Constructor for class org.apache.mahout.fpm.pfpgrowth.convertors.string.StringOutputConverter
 
StringParameter - Class in org.apache.mahout.common.parameters
 
StringParameter(String, String, Configuration, String, String) - Constructor for class org.apache.mahout.common.parameters.StringParameter
 
StringRecordIterator - Class in org.apache.mahout.common.iterator
 
StringRecordIterator(Iterable<String>, String) - Constructor for class org.apache.mahout.common.iterator.StringRecordIterator
 
StringTuple - Class in org.apache.mahout.common
An Ordered List of Strings which can be used in a Hadoop Map/Reduce Job
StringTuple() - Constructor for class org.apache.mahout.common.StringTuple
 
StringTuple(String) - Constructor for class org.apache.mahout.common.StringTuple
 
StringTuple(Iterable<String>) - Constructor for class org.apache.mahout.common.StringTuple
 
StringTuple(String[]) - Constructor for class org.apache.mahout.common.StringTuple
 
StringUtils - Class in org.apache.mahout.common
Offers two methods to convert an object to a string representation and restore the object given its string representation.
SUBGRAM_OUTPUT_DIRECTORY - Static variable in class org.apache.mahout.vectorizer.collocations.llr.CollocDriver
 
subset(Condition) - Method in class org.apache.mahout.classifier.df.data.Data
 
sum(int[]) - Static method in class org.apache.mahout.classifier.df.data.DataUtils
Computes the sum of the values
SUM - Static variable in class org.apache.mahout.math.hadoop.stats.StandardDeviationCalculatorMapper
 
SUM_OF_SQUARES - Static variable in class org.apache.mahout.math.hadoop.stats.StandardDeviationCalculatorMapper
 
summary(int) - Method in class org.apache.mahout.classifier.sgd.ModelDissector
Returns the n most important features with their weights, most important category and the top few categories that they affect.
SUMMED_OBSERVATIONS - Static variable in class org.apache.mahout.classifier.naivebayes.training.TrainNaiveBayesJob
 
support() - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.Pattern
 
SVDRecommender - Class in org.apache.mahout.cf.taste.impl.recommender.svd
A Recommender that uses matrix factorization (a projection of users and items onto a feature space)
SVDRecommender(DataModel, Factorizer) - Constructor for class org.apache.mahout.cf.taste.impl.recommender.svd.SVDRecommender
 
SVDRecommender(DataModel, Factorizer, CandidateItemsStrategy) - Constructor for class org.apache.mahout.cf.taste.impl.recommender.svd.SVDRecommender
 
SVDRecommender(DataModel, Factorizer, PersistenceStrategy) - Constructor for class org.apache.mahout.cf.taste.impl.recommender.svd.SVDRecommender
Create an SVDRecommender using a persistent store to cache factorizations.
SVDRecommender(DataModel, Factorizer, CandidateItemsStrategy, PersistenceStrategy) - Constructor for class org.apache.mahout.cf.taste.impl.recommender.svd.SVDRecommender
Create an SVDRecommender using a persistent store to cache factorizations.
swap() - Method in class org.apache.mahout.common.LongPair
 
swap() - Method in class org.apache.mahout.common.Pair
 

T

T1_KEY - Static variable in interface org.apache.mahout.clustering.canopy.CanopyConfigKeys
 
T1_KEY - Static variable in interface org.apache.mahout.clustering.meanshift.MeanShiftCanopyConfigKeys
 
T1_OPTION - Static variable in class org.apache.mahout.common.commandline.DefaultOptionCreator
 
t1Option() - Static method in class org.apache.mahout.common.commandline.DefaultOptionCreator
Returns a default command line option for specification of T1.
T2_KEY - Static variable in interface org.apache.mahout.clustering.canopy.CanopyConfigKeys
 
T2_KEY - Static variable in interface org.apache.mahout.clustering.meanshift.MeanShiftCanopyConfigKeys
 
T2_OPTION - Static variable in class org.apache.mahout.common.commandline.DefaultOptionCreator
 
t2Option() - Static method in class org.apache.mahout.common.commandline.DefaultOptionCreator
Returns a default command line option for specification of T2.
T3_KEY - Static variable in interface org.apache.mahout.clustering.canopy.CanopyConfigKeys
 
T3_OPTION - Static variable in class org.apache.mahout.common.commandline.DefaultOptionCreator
 
t3Option() - Static method in class org.apache.mahout.common.commandline.DefaultOptionCreator
Returns a default command line option for specification of T3 (Reducer T1).
T4_KEY - Static variable in interface org.apache.mahout.clustering.canopy.CanopyConfigKeys
 
T4_OPTION - Static variable in class org.apache.mahout.common.commandline.DefaultOptionCreator
 
t4Option() - Static method in class org.apache.mahout.common.commandline.DefaultOptionCreator
Returns a default command line option for specification of T4 (Reducer T2).
TanimotoCoefficientSimilarity - Class in org.apache.mahout.cf.taste.impl.similarity
An implementation of a "similarity" based on the Tanimoto coefficient, or extended Jaccard coefficient.
TanimotoCoefficientSimilarity(DataModel) - Constructor for class org.apache.mahout.cf.taste.impl.similarity.TanimotoCoefficientSimilarity
 
TanimotoCoefficientSimilarity - Class in org.apache.mahout.math.hadoop.similarity.cooccurrence.measures
 
TanimotoCoefficientSimilarity() - Constructor for class org.apache.mahout.math.hadoop.similarity.cooccurrence.measures.TanimotoCoefficientSimilarity
 
TanimotoDistanceMeasure - Class in org.apache.mahout.common.distance
Tanimoto coefficient implementation.
TanimotoDistanceMeasure() - Constructor for class org.apache.mahout.common.distance.TanimotoDistanceMeasure
 
TasteException - Exception in org.apache.mahout.cf.taste.common
An exception thrown when an error occurs inside the Taste engine.
TasteException() - Constructor for exception org.apache.mahout.cf.taste.common.TasteException
 
TasteException(String) - Constructor for exception org.apache.mahout.cf.taste.common.TasteException
 
TasteException(Throwable) - Constructor for exception org.apache.mahout.cf.taste.common.TasteException
 
TasteException(String, Throwable) - Constructor for exception org.apache.mahout.cf.taste.common.TasteException
 
TasteHadoopUtils - Class in org.apache.mahout.cf.taste.hadoop
Some helper methods for the hadoop-related stuff in org.apache.mahout.cf.taste
TAU - Static variable in interface org.apache.mahout.clustering.spectral.eigencuts.EigencutsKeys
Tau, or the user-specified threshold for making cuts (setting edge affinities to 0) after performing non-maximal suppression on edge weight sensitivies.
TAU_DEFAULT - Static variable in class org.apache.mahout.clustering.spectral.eigencuts.EigencutsDriver
 
TEMP_USER_ID - Static variable in class org.apache.mahout.cf.taste.impl.model.PlusAnonymousUserDataModel
 
TERM_TOPIC_SMOOTHING - Static variable in class org.apache.mahout.clustering.lda.cvb.CVB0Driver
 
TermCountCombiner - Class in org.apache.mahout.vectorizer.term
 
TermCountCombiner() - Constructor for class org.apache.mahout.vectorizer.term.TermCountCombiner
 
TermCountMapper - Class in org.apache.mahout.vectorizer.term
TextVectorizer Term Count Mapper.
TermCountMapper() - Constructor for class org.apache.mahout.vectorizer.term.TermCountMapper
 
TermCountReducer - Class in org.apache.mahout.vectorizer.term
This accumulates all the words and the weights and sums them up.
TermCountReducer() - Constructor for class org.apache.mahout.vectorizer.term.TermCountReducer
 
TermDocumentCountMapper - Class in org.apache.mahout.vectorizer.term
TextVectorizer Document Frequency Count Mapper.
TermDocumentCountMapper() - Constructor for class org.apache.mahout.vectorizer.term.TermDocumentCountMapper
 
TermDocumentCountReducer - Class in org.apache.mahout.vectorizer.term
Can also be used as a local Combiner.
TermDocumentCountReducer() - Constructor for class org.apache.mahout.vectorizer.term.TermDocumentCountReducer
 
TEST_SET_FRACTION - Static variable in class org.apache.mahout.clustering.lda.cvb.CVB0Driver
 
testBlockQrWithSSVD(int, int, int, long) - Static method in class org.apache.mahout.math.hadoop.stochasticsvd.SSVDPrototype
 
TestClassifier - Class in org.apache.mahout.classifier.bayes
Test the Naive Bayes classifier with improved weighting

To run the twenty newsgroups example: refer http://cwiki.apache.org/MAHOUT/twentynewsgroups.html

testConvergence(Iterable<SoftCluster>) - Method in class org.apache.mahout.clustering.fuzzykmeans.FuzzyKMeansClusterer
 
testConvergence(Iterable<Cluster>, double) - Method in class org.apache.mahout.clustering.kmeans.KMeansClusterer
Sequential implementation to test convergence and update cluster centers
TestNaiveBayesDriver - Class in org.apache.mahout.classifier.naivebayes.test
Test the (Complementary) Naive Bayes model that was built during training by running the iterating the test set and comparing it to the model
TestNaiveBayesDriver() - Constructor for class org.apache.mahout.classifier.naivebayes.test.TestNaiveBayesDriver
 
testThinQr(int, int) - Static method in class org.apache.mahout.math.hadoop.stochasticsvd.SSVDPrototype
 
TextValueEncoder - Class in org.apache.mahout.vectorizer.encoders
Encodes text that is tokenized on non-alphanum separators.
TextValueEncoder(String) - Constructor for class org.apache.mahout.vectorizer.encoders.TextValueEncoder
 
TF - Class in org.apache.mahout.vectorizer
Weight based on term frequency only
TF() - Constructor for class org.apache.mahout.vectorizer.TF
 
TFIDF - Class in org.apache.mahout.vectorizer
 
TFIDF() - Constructor for class org.apache.mahout.vectorizer.TFIDF
 
TFIDF(Similarity) - Constructor for class org.apache.mahout.vectorizer.TFIDF
 
TFIDFConverter - Class in org.apache.mahout.vectorizer.tfidf
This class converts a set of input vectors with term frequencies to TfIdf vectors.
TFIDFPartialVectorReducer - Class in org.apache.mahout.vectorizer.tfidf
Converts a document in to a sparse vector
TFIDFPartialVectorReducer() - Constructor for class org.apache.mahout.vectorizer.tfidf.TFIDFPartialVectorReducer
 
TFPartialVectorReducer - Class in org.apache.mahout.vectorizer.term
Converts a document in to a sparse vector
TFPartialVectorReducer() - Constructor for class org.apache.mahout.vectorizer.term.TFPartialVectorReducer
 
ThetaMapper - Class in org.apache.mahout.classifier.naivebayes.training
 
ThetaMapper() - Constructor for class org.apache.mahout.classifier.naivebayes.training.ThetaMapper
 
thetaNormalizer(int) - Method in class org.apache.mahout.classifier.naivebayes.NaiveBayesModel
 
THETAS - Static variable in class org.apache.mahout.classifier.naivebayes.training.TrainNaiveBayesJob
 
THRESHOLD_KEY - Static variable in class org.apache.mahout.clustering.dirichlet.DirichletDriver
 
THRESHOLD_KEY - Static variable in interface org.apache.mahout.clustering.fuzzykmeans.FuzzyKMeansConfigKeys
 
THRESHOLD_OPTION - Static variable in class org.apache.mahout.common.commandline.DefaultOptionCreator
 
thresholdOption() - Static method in class org.apache.mahout.common.commandline.DefaultOptionCreator
Returns a default command line option for specifying the clustering threshold value.
ThresholdUserNeighborhood - Class in org.apache.mahout.cf.taste.impl.neighborhood
Computes a neigbhorhood consisting of all users whose similarity to the given user meets or exceeds a certain threshold.
ThresholdUserNeighborhood(double, UserSimilarity, DataModel) - Constructor for class org.apache.mahout.cf.taste.impl.neighborhood.ThresholdUserNeighborhood
 
ThresholdUserNeighborhood(double, UserSimilarity, DataModel, double) - Constructor for class org.apache.mahout.cf.taste.impl.neighborhood.ThresholdUserNeighborhood
 
times(DistributedRowMatrix) - Method in class org.apache.mahout.math.hadoop.DistributedRowMatrix
This implements matrix this.transpose().times(other)
times(Vector) - Method in class org.apache.mahout.math.hadoop.DistributedRowMatrix
 
timesDelta(int, double) - Method in class org.apache.mahout.classifier.discriminative.LinearModel
Multiply the weight at index by delta.
timesSquared(Vector) - Method in class org.apache.mahout.math.hadoop.DistributedRowMatrix
 
TimesSquaredJob - Class in org.apache.mahout.math.hadoop
 
TimesSquaredJob.TimesMapper - Class in org.apache.mahout.math.hadoop
 
TimesSquaredJob.TimesMapper() - Constructor for class org.apache.mahout.math.hadoop.TimesSquaredJob.TimesMapper
 
TimesSquaredJob.TimesSquaredMapper<T extends org.apache.hadoop.io.WritableComparable> - Class in org.apache.mahout.math.hadoop
 
TimesSquaredJob.TimesSquaredMapper() - Constructor for class org.apache.mahout.math.hadoop.TimesSquaredJob.TimesSquaredMapper
 
TimesSquaredJob.VectorSummingReducer - Class in org.apache.mahout.math.hadoop
 
TimesSquaredJob.VectorSummingReducer() - Constructor for class org.apache.mahout.math.hadoop.TimesSquaredJob.VectorSummingReducer
 
TimingStatistics - Class in org.apache.mahout.common
 
TimingStatistics() - Constructor for class org.apache.mahout.common.TimingStatistics
Creates a new instance of CallStats
TimingStatistics(int, long, long, long, double) - Constructor for class org.apache.mahout.common.TimingStatistics
 
TimingStatistics.Call - Class in org.apache.mahout.common
 
toArray() - Method in class org.apache.mahout.cf.taste.impl.common.FastIDSet
 
toArray(VectorWritable) - Static method in class org.apache.mahout.math.hadoop.similarity.cooccurrence.Vectors
 
toDataMap(DataModel) - Static method in class org.apache.mahout.cf.taste.impl.model.GenericBooleanPrefDataModel
Exports the simple user IDs and associated item IDs in the data model.
toDataMap(FastByIDMap<PreferenceArray>) - Static method in class org.apache.mahout.cf.taste.impl.model.GenericBooleanPrefDataModel
 
toDataMap(FastByIDMap<Collection<Preference>>, boolean) - Static method in class org.apache.mahout.cf.taste.impl.model.GenericDataModel
Swaps, in-place, Lists for arrays in Map values .
toDataMap(DataModel) - Static method in class org.apache.mahout.cf.taste.impl.model.GenericDataModel
Exports the simple user IDs and preferences in the data model.
ToEntityPrefsMapper - Class in org.apache.mahout.cf.taste.hadoop
 
ToItemPrefsMapper - Class in org.apache.mahout.cf.taste.hadoop
Input
ToItemPrefsMapper() - Constructor for class org.apache.mahout.cf.taste.hadoop.ToItemPrefsMapper
 
ToItemVectorsMapper - Class in org.apache.mahout.cf.taste.hadoop.preparation
 
ToItemVectorsMapper() - Constructor for class org.apache.mahout.cf.taste.hadoop.preparation.ToItemVectorsMapper
 
ToItemVectorsReducer - Class in org.apache.mahout.cf.taste.hadoop.preparation
 
ToItemVectorsReducer() - Constructor for class org.apache.mahout.cf.taste.hadoop.preparation.ToItemVectorsReducer
 
tokenize(CharSequence) - Method in class org.apache.mahout.vectorizer.encoders.LuceneTextValueEncoder
Tokenizes a string using the simplest method.
tokenize(CharSequence) - Method in class org.apache.mahout.vectorizer.encoders.TextValueEncoder
Tokenizes a string using the simplest method.
TOKENIZED_DOCUMENT_OUTPUT_FOLDER - Static variable in class org.apache.mahout.vectorizer.DocumentProcessor
 
tokenizeDocuments(Path, Class<? extends Analyzer>, Path, Configuration) - Static method in class org.apache.mahout.vectorizer.DocumentProcessor
Convert the input documents into token array using the StringTuple The input documents has to be in the SequenceFile format
tokenStream(String, Reader) - Method in class org.apache.mahout.vectorizer.DefaultAnalyzer
 
TokenStreamIterator - Class in org.apache.mahout.common.lucene
Provide an Iterator for the tokens in a TokenStream.
TokenStreamIterator(TokenStream) - Constructor for class org.apache.mahout.common.lucene.TokenStreamIterator
 
toLongID(String) - Method in class org.apache.mahout.cf.taste.impl.model.AbstractIDMigrator
 
toLongID(String) - Method in interface org.apache.mahout.cf.taste.model.IDMigrator
 
TOP_LEVEL_CLUSTER_DIRECTORY - Static variable in class org.apache.mahout.clustering.topdown.PathDirectory
 
TopicModel - Class in org.apache.mahout.clustering.lda.cvb
Thin wrapper around a Matrix of counts of occurrences of (topic, term) pairs.
TopicModel(int, int, double, double, String[], double) - Constructor for class org.apache.mahout.clustering.lda.cvb.TopicModel
 
TopicModel(Configuration, double, double, String[], int, double, Path...) - Constructor for class org.apache.mahout.clustering.lda.cvb.TopicModel
 
TopicModel(int, int, double, double, String[], int, double) - Constructor for class org.apache.mahout.clustering.lda.cvb.TopicModel
 
TopicModel(int, int, double, double, Random, String[], int, double) - Constructor for class org.apache.mahout.clustering.lda.cvb.TopicModel
 
TopicModel(Matrix, Vector, double, double, String[], double) - Constructor for class org.apache.mahout.clustering.lda.cvb.TopicModel
 
TopicModel(Matrix, double, double, String[], int, double) - Constructor for class org.apache.mahout.clustering.lda.cvb.TopicModel
 
TopicModel(Matrix, Vector, double, double, String[], int, double) - Constructor for class org.apache.mahout.clustering.lda.cvb.TopicModel
 
topicSums() - Method in class org.apache.mahout.clustering.lda.cvb.TopicModel
 
TopItems - Class in org.apache.mahout.cf.taste.impl.recommender
A simple class that refactors the "find top N things" logic that is used in several places.
TopItems.Estimator<T> - Interface in org.apache.mahout.cf.taste.impl.recommender
 
TopK<T> - Class in org.apache.mahout.cf.taste.common
this class will preserve the k maximum elements of all elements it has been offered
TopK(int, Comparator<? super T>) - Constructor for class org.apache.mahout.cf.taste.common.TopK
 
topKElements(int, Vector) - Static method in class org.apache.mahout.math.hadoop.similarity.cooccurrence.Vectors
 
TopKPatternsOutputConverter<A extends Comparable<? super A>> - Class in org.apache.mahout.fpm.pfpgrowth.convertors
An output converter which converts the output patterns and collects them in a FrequentPatternMaxHeap
TopKPatternsOutputConverter(OutputCollector<A, List<Pair<List<A>, Long>>>, Map<Integer, A>) - Constructor for class org.apache.mahout.fpm.pfpgrowth.convertors.TopKPatternsOutputConverter
 
TopKStringPatterns - Class in org.apache.mahout.fpm.pfpgrowth.convertors.string
A class which collects Top K string patterns
TopKStringPatterns() - Constructor for class org.apache.mahout.fpm.pfpgrowth.convertors.string.TopKStringPatterns
 
TopKStringPatterns(Collection<Pair<List<String>, Long>>) - Constructor for class org.apache.mahout.fpm.pfpgrowth.convertors.string.TopKStringPatterns
 
toRho(double, double) - Static method in class org.apache.mahout.math.hadoop.stochasticsvd.qr.GivensThinSolver
 
toString() - Method in class org.apache.mahout.cf.taste.hadoop.EntityCountWritable
 
toString() - Method in class org.apache.mahout.cf.taste.hadoop.EntityEntityWritable
 
toString() - Method in class org.apache.mahout.cf.taste.hadoop.EntityPrefWritable
 
toString() - Method in class org.apache.mahout.cf.taste.hadoop.EntityPrefWritableArrayWritable
 
toString() - Method in class org.apache.mahout.cf.taste.hadoop.item.VectorAndPrefsWritable
 
toString() - Method in class org.apache.mahout.cf.taste.hadoop.item.VectorOrPrefWritable
 
toString() - Method in class org.apache.mahout.cf.taste.hadoop.RecommendedItemsWritable
 
toString() - Method in class org.apache.mahout.cf.taste.hadoop.slopeone.FullRunningAverageAndStdDevWritable
 
toString() - Method in class org.apache.mahout.cf.taste.impl.common.Cache
 
toString() - Method in class org.apache.mahout.cf.taste.impl.common.FastByIDMap
 
toString() - Method in class org.apache.mahout.cf.taste.impl.common.FastIDSet
 
toString() - Method in class org.apache.mahout.cf.taste.impl.common.FastMap
 
toString() - Method in class org.apache.mahout.cf.taste.impl.common.FixedRunningAverage
 
toString() - Method in class org.apache.mahout.cf.taste.impl.common.FixedRunningAverageAndStdDev
 
toString() - Method in class org.apache.mahout.cf.taste.impl.common.FullRunningAverage
 
toString() - Method in class org.apache.mahout.cf.taste.impl.common.FullRunningAverageAndStdDev
 
toString() - Method in class org.apache.mahout.cf.taste.impl.common.LongPrimitiveArrayIterator
 
toString() - Method in class org.apache.mahout.cf.taste.impl.common.WeightedRunningAverage
 
toString() - Method in class org.apache.mahout.cf.taste.impl.common.WeightedRunningAverageAndStdDev
 
toString() - Method in class org.apache.mahout.cf.taste.impl.eval.AverageAbsoluteDifferenceRecommenderEvaluator
 
toString() - Method in class org.apache.mahout.cf.taste.impl.eval.IRStatisticsImpl
 
toString() - Method in class org.apache.mahout.cf.taste.impl.eval.RMSRecommenderEvaluator
 
toString() - Method in class org.apache.mahout.cf.taste.impl.model.BooleanItemPreferenceArray
 
toString() - Method in class org.apache.mahout.cf.taste.impl.model.BooleanPreference
 
toString() - Method in class org.apache.mahout.cf.taste.impl.model.BooleanUserPreferenceArray
 
toString() - Method in class org.apache.mahout.cf.taste.impl.model.file.FileDataModel
 
toString() - Method in class org.apache.mahout.cf.taste.impl.model.file.FileIDMigrator
 
toString() - Method in class org.apache.mahout.cf.taste.impl.model.GenericBooleanPrefDataModel
 
toString() - Method in class org.apache.mahout.cf.taste.impl.model.GenericDataModel
 
toString() - Method in class org.apache.mahout.cf.taste.impl.model.GenericItemPreferenceArray
 
toString() - Method in class org.apache.mahout.cf.taste.impl.model.GenericPreference
 
toString() - Method in class org.apache.mahout.cf.taste.impl.model.GenericUserPreferenceArray
 
toString() - Method in class org.apache.mahout.cf.taste.impl.neighborhood.NearestNUserNeighborhood
 
toString() - Method in class org.apache.mahout.cf.taste.impl.neighborhood.ThresholdUserNeighborhood
 
toString() - Method in class org.apache.mahout.cf.taste.impl.recommender.CachingRecommender
 
toString() - Method in class org.apache.mahout.cf.taste.impl.recommender.FarthestNeighborClusterSimilarity
 
toString() - Method in class org.apache.mahout.cf.taste.impl.recommender.GenericBooleanPrefItemBasedRecommender
 
toString() - Method in class org.apache.mahout.cf.taste.impl.recommender.GenericBooleanPrefUserBasedRecommender
 
toString() - Method in class org.apache.mahout.cf.taste.impl.recommender.GenericItemBasedRecommender
 
toString() - Method in class org.apache.mahout.cf.taste.impl.recommender.GenericRecommendedItem
 
toString() - Method in class org.apache.mahout.cf.taste.impl.recommender.GenericUserBasedRecommender
 
toString() - Method in class org.apache.mahout.cf.taste.impl.recommender.ItemAverageRecommender
 
toString() - Method in class org.apache.mahout.cf.taste.impl.recommender.ItemUserAverageRecommender
 
toString() - Method in class org.apache.mahout.cf.taste.impl.recommender.NearestNeighborClusterSimilarity
 
toString() - Method in class org.apache.mahout.cf.taste.impl.recommender.NullRescorer
 
toString() - Method in class org.apache.mahout.cf.taste.impl.recommender.SimilarUser
 
toString() - Method in class org.apache.mahout.cf.taste.impl.recommender.slopeone.MemoryDiffStorage
 
toString() - Method in class org.apache.mahout.cf.taste.impl.recommender.slopeone.SlopeOneRecommender
 
toString() - Method in class org.apache.mahout.cf.taste.impl.recommender.TreeClusteringRecommender
 
toString() - Method in class org.apache.mahout.cf.taste.impl.recommender.TreeClusteringRecommender2
 
toString() - Method in class org.apache.mahout.cf.taste.impl.similarity.AveragingPreferenceInferrer
 
toString() - Method in class org.apache.mahout.cf.taste.impl.similarity.file.FileItemSimilarity
 
toString() - Method in class org.apache.mahout.cf.taste.impl.similarity.GenericItemSimilarity.ItemItemSimilarity
 
toString() - Method in class org.apache.mahout.cf.taste.impl.similarity.GenericUserSimilarity.UserUserSimilarity
 
toString() - Method in class org.apache.mahout.cf.taste.impl.similarity.LogLikelihoodSimilarity
 
toString() - Method in class org.apache.mahout.cf.taste.impl.similarity.TanimotoCoefficientSimilarity
 
toString() - Method in class org.apache.mahout.cf.taste.impl.transforms.CaseAmplification
 
toString() - Method in class org.apache.mahout.cf.taste.impl.transforms.InverseUserFrequency
 
toString() - Method in class org.apache.mahout.cf.taste.impl.transforms.ZScore
 
toString() - Method in class org.apache.mahout.classifier.ClassifierResult
 
toString() - Method in class org.apache.mahout.classifier.ConfusionMatrix
This is overloaded.
toString() - Method in class org.apache.mahout.classifier.df.mapreduce.inmem.InMemInputFormat.InMemInputSplit
 
toString() - Method in class org.apache.mahout.classifier.df.mapreduce.MapredOutput
 
toString() - Method in class org.apache.mahout.classifier.df.node.Node
 
toString() - Method in class org.apache.mahout.classifier.df.split.Split
 
toString(DecisionForest, Dataset, String[]) - Static method in class org.apache.mahout.classifier.df.tools.ForestVisualizer
 
toString(String, String, String[]) - Static method in class org.apache.mahout.classifier.df.tools.ForestVisualizer
Decision Forest to String
toString(Node, Dataset, String[]) - Static method in class org.apache.mahout.classifier.df.tools.TreeVisualizer
Decision tree to String
toString() - Method in class org.apache.mahout.classifier.discriminative.LinearModel
 
toString() - Method in class org.apache.mahout.classifier.RegressionResultAnalyzer
 
toString() - Method in class org.apache.mahout.classifier.ResultAnalyzer
 
toString() - Method in class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression.Wrapper
 
toString() - Method in class org.apache.mahout.clustering.canopy.Canopy
 
toString() - Method in class org.apache.mahout.clustering.ClusterObservations
 
toString() - Method in class org.apache.mahout.clustering.dirichlet.models.DistributionDescription
 
toString() - Method in class org.apache.mahout.clustering.kmeans.Cluster
 
toString() - Method in class org.apache.mahout.clustering.lda.cvb.TopicModel
 
toString() - Method in class org.apache.mahout.clustering.WeightedPropertyVectorWritable
 
toString() - Method in class org.apache.mahout.clustering.WeightedVectorWritable
 
toString() - Method in class org.apache.mahout.common.IntegerTuple
 
toString() - Method in class org.apache.mahout.common.IntPairWritable.Frequency
 
toString() - Method in class org.apache.mahout.common.IntPairWritable
 
toString() - Method in class org.apache.mahout.common.LongPair
 
toString() - Method in class org.apache.mahout.common.Pair
 
toString() - Method in class org.apache.mahout.common.parameters.AbstractParameter
 
toString() - Method in class org.apache.mahout.common.Parameters
 
toString() - Method in class org.apache.mahout.common.StringTuple
 
toString(Object) - Static method in class org.apache.mahout.common.StringUtils
Converts the object to a one-line string representation
toString() - Method in class org.apache.mahout.common.TimingStatistics
 
toString() - Method in class org.apache.mahout.ep.State
 
toString() - Method in class org.apache.mahout.fpm.pfpgrowth.convertors.string.TopKStringPatterns
 
toString() - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.FPTree
 
toString() - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.FrequentPatternMaxHeap
 
toString() - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth.Pattern
 
toString() - Method in class org.apache.mahout.fpm.pfpgrowth.fpgrowth2.FPTree
 
toString() - Method in class org.apache.mahout.math.hadoop.DistributedRowMatrix.MatrixEntryWritable
 
toString() - Method in class org.apache.mahout.math.VarIntWritable
 
toString() - Method in class org.apache.mahout.math.VarLongWritable
 
toString() - Method in class org.apache.mahout.math.VectorWritable
 
toString() - Method in class org.apache.mahout.vectorizer.collocations.llr.Gram
 
toString() - Method in enum org.apache.mahout.vectorizer.collocations.llr.Gram.Type
 
toString() - Method in class org.apache.mahout.vectorizer.collocations.llr.GramKey
 
toStringID(long) - Method in class org.apache.mahout.cf.taste.impl.model.AbstractJDBCIDMigrator
 
toStringID(long) - Method in class org.apache.mahout.cf.taste.impl.model.file.FileIDMigrator
 
toStringID(long) - Method in class org.apache.mahout.cf.taste.impl.model.MemoryIDMigrator
 
toStringID(long) - Method in interface org.apache.mahout.cf.taste.model.IDMigrator
 
TOTAL_COUNT - Static variable in class org.apache.mahout.math.hadoop.stats.StandardDeviationCalculatorMapper
 
TOTAL_SUM - Static variable in class org.apache.mahout.classifier.bayes.mapreduce.common.BayesConstants
 
totalCounts() - Method in class org.apache.mahout.clustering.dirichlet.DirichletState
 
totalWeightSum() - Method in class org.apache.mahout.classifier.naivebayes.NaiveBayesModel
 
totalWeightSum() - Method in class org.apache.mahout.classifier.naivebayes.training.AbstractThetaTrainer
 
ToUserPrefsMapper - Class in org.apache.mahout.cf.taste.hadoop
The 'reverse' of ToItemPrefsMapper; outputs item IDs mapped to user-pref data.
ToUserPrefsMapper() - Constructor for class org.apache.mahout.cf.taste.hadoop.ToUserPrefsMapper
 
ToUserVectorsReducer - Class in org.apache.mahout.cf.taste.hadoop.item
Input
ToUserVectorsReducer() - Constructor for class org.apache.mahout.cf.taste.hadoop.item.ToUserVectorsReducer
 
ToUserVectorsReducer.Counters - Enum in org.apache.mahout.cf.taste.hadoop.item
 
ToVectorAndPrefReducer - Class in org.apache.mahout.cf.taste.hadoop.item
 
ToVectorAndPrefReducer() - Constructor for class org.apache.mahout.cf.taste.hadoop.item.ToVectorAndPrefReducer
 
TPrior - Class in org.apache.mahout.classifier.sgd
Provides a t-distribution as a prior.
TPrior(double) - Constructor for class org.apache.mahout.classifier.sgd.TPrior
 
trace(String, int) - Method in class org.apache.mahout.vectorizer.encoders.FeatureVectorEncoder
 
trace(byte[], int) - Method in class org.apache.mahout.vectorizer.encoders.FeatureVectorEncoder
 
train(Vector, Matrix) - Method in class org.apache.mahout.classifier.discriminative.LinearTrainer
Initializes training.
train(int, Vector) - Method in class org.apache.mahout.classifier.naivebayes.training.AbstractThetaTrainer
 
train(int, Vector) - Method in class org.apache.mahout.classifier.naivebayes.training.ComplementaryThetaTrainer
 
train(int, Vector) - Method in class org.apache.mahout.classifier.naivebayes.training.StandardThetaTrainer
 
train(int, Vector) - Method in interface org.apache.mahout.classifier.OnlineLearner
Updates the model using a particular target variable value and a feature vector.
train(long, String, int, Vector) - Method in interface org.apache.mahout.classifier.OnlineLearner
Updates the model using a particular target variable value and a feature vector.
train(long, int, Vector) - Method in interface org.apache.mahout.classifier.OnlineLearner
Updates the model using a particular target variable value and a feature vector.
train(long, String, int, Vector) - Method in class org.apache.mahout.classifier.sgd.AbstractOnlineLogisticRegression
 
train(long, int, Vector) - Method in class org.apache.mahout.classifier.sgd.AbstractOnlineLogisticRegression
 
train(int, Vector) - Method in class org.apache.mahout.classifier.sgd.AbstractOnlineLogisticRegression
 
train(int, Vector) - Method in class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression
 
train(long, int, Vector) - Method in class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression
 
train(long, String, int, Vector) - Method in class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression
 
train(AdaptiveLogisticRegression.TrainingExample) - Method in class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression.Wrapper
 
train(int, Vector) - Method in class org.apache.mahout.classifier.sgd.CrossFoldLearner
 
train(long, int, Vector) - Method in class org.apache.mahout.classifier.sgd.CrossFoldLearner
 
train(long, String, int, Vector) - Method in class org.apache.mahout.classifier.sgd.CrossFoldLearner
 
train(long, String, int, Vector) - Method in class org.apache.mahout.classifier.sgd.GradientMachine
 
train(long, int, Vector) - Method in class org.apache.mahout.classifier.sgd.GradientMachine
 
train(int, Vector) - Method in class org.apache.mahout.classifier.sgd.GradientMachine
 
train(long, String, int, Vector) - Method in class org.apache.mahout.classifier.sgd.PassiveAggressive
 
train(long, int, Vector) - Method in class org.apache.mahout.classifier.sgd.PassiveAggressive
 
train(int, Vector) - Method in class org.apache.mahout.classifier.sgd.PassiveAggressive
 
train(int, Vector) - Method in class org.apache.mahout.clustering.ClusterClassifier
 
train(int, Vector, double) - Method in class org.apache.mahout.clustering.ClusterClassifier
Train the models given an additional weight.
train(long, String, int, Vector) - Method in class org.apache.mahout.clustering.ClusterClassifier
 
train(long, int, Vector) - Method in class org.apache.mahout.clustering.ClusterClassifier
 
train(VectorIterable, VectorIterable) - Method in class org.apache.mahout.clustering.lda.cvb.ModelTrainer
 
train(VectorIterable, VectorIterable, int) - Method in class org.apache.mahout.clustering.lda.cvb.ModelTrainer
 
train(Vector, Vector, boolean, int) - Method in class org.apache.mahout.clustering.lda.cvb.ModelTrainer
 
trainBaumWelch(HmmModel, int[], double, int, boolean) - Static method in class org.apache.mahout.classifier.sequencelearning.hmm.HmmTrainer
Iteratively train the parameters of the given initial model wrt the observed sequence using Baum-Welch training.
TrainClassifier - Class in org.apache.mahout.classifier.bayes
Train the Naive Bayes classifier with improved weighting.
trainCNaiveBayes(Path, Path, BayesParameters) - Static method in class org.apache.mahout.classifier.bayes.TrainClassifier
 
trainDocTopicModel(Vector, Vector, Matrix) - Method in class org.apache.mahout.clustering.lda.cvb.TopicModel
 
trainDocuments() - Method in class org.apache.mahout.clustering.lda.cvb.InMemoryCollapsedVariationalBayes0
 
trainDocuments(double) - Method in class org.apache.mahout.clustering.lda.cvb.InMemoryCollapsedVariationalBayes0
 
TrainingException - Exception in org.apache.mahout.classifier.discriminative
This exception is thrown in case training fails.
TrainingException(String) - Constructor for exception org.apache.mahout.classifier.discriminative.TrainingException
Init with message string describing the cause of the exception.
trainNaiveBayes(Path, Path, BayesParameters) - Static method in class org.apache.mahout.classifier.bayes.TrainClassifier
 
TrainNaiveBayesJob - Class in org.apache.mahout.classifier.naivebayes.training
This class trains a Naive Bayes Classifier (Parameters for both Naive Bayes and Complementary Naive Bayes)
TrainNaiveBayesJob() - Constructor for class org.apache.mahout.classifier.naivebayes.training.TrainNaiveBayesJob
 
trainSupervised(int, int, int[], int[], double) - Static method in class org.apache.mahout.classifier.sequencelearning.hmm.HmmTrainer
Create an supervised initial estimate of an HMM Model based on a sequence of observed and hidden states.
trainSupervisedSequence(int, int, Collection<int[]>, Collection<int[]>, double) - Static method in class org.apache.mahout.classifier.sequencelearning.hmm.HmmTrainer
Create an supervised initial estimate of an HMM Model based on a number of sequences of observed and hidden states.
trainSync(Vector, Vector, boolean, int) - Method in class org.apache.mahout.clustering.lda.cvb.ModelTrainer
 
trainViterbi(HmmModel, int[], double, double, int, boolean) - Static method in class org.apache.mahout.classifier.sequencelearning.hmm.HmmTrainer
Iteratively train the parameters of the given initial model wrt to the observed sequence using Viterbi training.
TransactionIterator<T> - Class in org.apache.mahout.fpm.pfpgrowth.convertors
Iterates over a Transaction and outputs the transaction integer id mapping and the support of the transaction
TransactionIterator(Iterator<Pair<List<T>, Long>>, Map<T, Integer>) - Constructor for class org.apache.mahout.fpm.pfpgrowth.convertors.TransactionIterator
 
TransactionTree - Class in org.apache.mahout.fpm.pfpgrowth
A compact representation of transactions modeled on the lines to FPTree This reduces plenty of space and speeds up Map/Reduce of PFPGrowth algorithm by reducing data size passed from the Mapper to the reducer where FPGrowth mining is done
TransactionTree() - Constructor for class org.apache.mahout.fpm.pfpgrowth.TransactionTree
 
TransactionTree(int) - Constructor for class org.apache.mahout.fpm.pfpgrowth.TransactionTree
 
TransactionTree(int[], Long) - Constructor for class org.apache.mahout.fpm.pfpgrowth.TransactionTree
 
TransactionTree(IntArrayList, Long) - Constructor for class org.apache.mahout.fpm.pfpgrowth.TransactionTree
 
TransactionTree(List<Pair<IntArrayList, Long>>) - Constructor for class org.apache.mahout.fpm.pfpgrowth.TransactionTree
 
transformSimilarity(long, long, double) - Method in class org.apache.mahout.cf.taste.impl.transforms.CaseAmplification
Transforms one similarity value.
transformSimilarity(long, long, double) - Method in interface org.apache.mahout.cf.taste.transforms.SimilarityTransform
 
transpose() - Method in class org.apache.mahout.math.hadoop.DistributedRowMatrix
 
TRANSPOSE_USER_ITEM - Static variable in class org.apache.mahout.cf.taste.hadoop.ToEntityPrefsMapper
 
TransposeJob - Class in org.apache.mahout.math.hadoop
Transpose a matrix
TransposeJob() - Constructor for class org.apache.mahout.math.hadoop.TransposeJob
 
TransposeJob.MergeVectorsCombiner - Class in org.apache.mahout.math.hadoop
 
TransposeJob.MergeVectorsCombiner() - Constructor for class org.apache.mahout.math.hadoop.TransposeJob.MergeVectorsCombiner
 
TransposeJob.MergeVectorsReducer - Class in org.apache.mahout.math.hadoop
 
TransposeJob.MergeVectorsReducer() - Constructor for class org.apache.mahout.math.hadoop.TransposeJob.MergeVectorsReducer
 
TransposeJob.TransposeMapper - Class in org.apache.mahout.math.hadoop
 
TransposeJob.TransposeMapper() - Constructor for class org.apache.mahout.math.hadoop.TransposeJob.TransposeMapper
 
TransposeMapper - Class in org.apache.mahout.common.mapreduce
 
TransposeMapper() - Constructor for class org.apache.mahout.common.mapreduce.TransposeMapper
 
TreeBuilder - Interface in org.apache.mahout.classifier.df.builder
Abstract base class for TreeBuilders
TreeClusteringRecommender - Class in org.apache.mahout.cf.taste.impl.recommender
A Recommender that clusters users, then determines the clusters' top recommendations.
TreeClusteringRecommender(DataModel, ClusterSimilarity, int) - Constructor for class org.apache.mahout.cf.taste.impl.recommender.TreeClusteringRecommender
 
TreeClusteringRecommender(DataModel, ClusterSimilarity, int, double) - Constructor for class org.apache.mahout.cf.taste.impl.recommender.TreeClusteringRecommender
 
TreeClusteringRecommender(DataModel, ClusterSimilarity, double) - Constructor for class org.apache.mahout.cf.taste.impl.recommender.TreeClusteringRecommender
 
TreeClusteringRecommender(DataModel, ClusterSimilarity, double, double) - Constructor for class org.apache.mahout.cf.taste.impl.recommender.TreeClusteringRecommender
 
TreeClusteringRecommender2 - Class in org.apache.mahout.cf.taste.impl.recommender
A Recommender that clusters users, then determines the clusters' top recommendations.
TreeClusteringRecommender2(DataModel, ClusterSimilarity, int) - Constructor for class org.apache.mahout.cf.taste.impl.recommender.TreeClusteringRecommender2
 
TreeClusteringRecommender2(DataModel, ClusterSimilarity, double) - Constructor for class org.apache.mahout.cf.taste.impl.recommender.TreeClusteringRecommender2
 
TreeID - Class in org.apache.mahout.classifier.df.mapreduce.partial
Indicates both the tree and the data partition used to grow the tree
TreeID() - Constructor for class org.apache.mahout.classifier.df.mapreduce.partial.TreeID
 
TreeID(int, int) - Constructor for class org.apache.mahout.classifier.df.mapreduce.partial.TreeID
 
treeId() - Method in class org.apache.mahout.classifier.df.mapreduce.partial.TreeID
 
TreeVisualizer - Class in org.apache.mahout.classifier.df.tools
This tool is to visualize the Decision tree
TriangularKernelProfile - Class in org.apache.mahout.common.kernel
 
TriangularKernelProfile() - Constructor for class org.apache.mahout.common.kernel.TriangularKernelProfile
 
trim() - Method in class org.apache.mahout.math.hadoop.stochasticsvd.qr.GivensThinSolver
 
truncateModel(HmmModel, double) - Static method in class org.apache.mahout.classifier.sequencelearning.hmm.HmmUtils
Method to reduce the size of an HMMmodel by converting the models DenseMatrix/DenseVectors to sparse implementations and setting every value < threshold to 0
type() - Method in class org.apache.mahout.common.parameters.AbstractParameter
 
type() - Method in interface org.apache.mahout.common.parameters.Parameter
 

U

UDistrib - Class in org.apache.mahout.classifier.df.tools
This tool is used to uniformly distribute the class of all the tuples of the dataset over a given number of partitions.
This class can be used when the criterion variable is the categorical attribute.
UJob - Class in org.apache.mahout.math.hadoop.stochasticsvd
Computes U=Q*Uhat of SSVD (optionally adding x pow(Sigma, 0.5) )
UJob() - Constructor for class org.apache.mahout.math.hadoop.stochasticsvd.UJob
 
UJob.UMapper - Class in org.apache.mahout.math.hadoop.stochasticsvd
 
UJob.UMapper() - Constructor for class org.apache.mahout.math.hadoop.stochasticsvd.UJob.UMapper
 
UncenteredCosineSimilarity - Class in org.apache.mahout.cf.taste.impl.similarity
An implementation of the cosine similarity.
UncenteredCosineSimilarity(DataModel) - Constructor for class org.apache.mahout.cf.taste.impl.similarity.UncenteredCosineSimilarity
 
UncenteredCosineSimilarity(DataModel, Weighting) - Constructor for class org.apache.mahout.cf.taste.impl.similarity.UncenteredCosineSimilarity
 
UncommonDistributions - Class in org.apache.mahout.clustering.dirichlet
 
UniformPrior - Class in org.apache.mahout.classifier.sgd
A uniform prior.
UniformPrior() - Constructor for class org.apache.mahout.classifier.sgd.UniformPrior
 
UnitVectorizerJob - Class in org.apache.mahout.clustering.spectral.common
Given a DistributedRowMatrix, this job normalizes each row to unit vector length.
UnitVectorizerJob.UnitVectorizerMapper - Class in org.apache.mahout.clustering.spectral.common
 
UnitVectorizerJob.UnitVectorizerMapper() - Constructor for class org.apache.mahout.clustering.spectral.common.UnitVectorizerJob.UnitVectorizerMapper
 
unseal() - Method in class org.apache.mahout.classifier.sgd.AbstractOnlineLogisticRegression
 
UpdatableIDMigrator - Interface in org.apache.mahout.cf.taste.model
 
update(double, Vector, LinearModel) - Method in class org.apache.mahout.classifier.discriminative.LinearTrainer
Implement this method to match your training strategy.
update(double, Vector, LinearModel) - Method in class org.apache.mahout.classifier.discriminative.PerceptronTrainer
Implement this method to match your training strategy.
update(double, Vector, LinearModel) - Method in class org.apache.mahout.classifier.discriminative.WinnowTrainer
Implement this method to match your training strategy.
update(double[]) - Method in class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression.Wrapper
 
update(Vector, Map<String, Set<Integer>>, AbstractVectorClassifier) - Method in class org.apache.mahout.classifier.sgd.ModelDissector
Probes a model to determine the effect of a particular variable.
update(ClusterClassifier) - Method in interface org.apache.mahout.clustering.ClusteringPolicy
Update the policy with the given classifier
update(Cluster[]) - Method in class org.apache.mahout.clustering.dirichlet.DirichletState
Update the receiver with the new models
update(ClusterClassifier) - Method in class org.apache.mahout.clustering.DirichletClusteringPolicy
 
update(ClusterClassifier) - Method in class org.apache.mahout.clustering.FuzzyKMeansClusteringPolicy
 
update(ClusterClassifier) - Method in class org.apache.mahout.clustering.KMeansClusteringPolicy
 
update(Matrix) - Method in class org.apache.mahout.clustering.lda.cvb.TopicModel
 
update(int, Vector) - Method in class org.apache.mahout.clustering.lda.cvb.TopicModel
 
update(double[]) - Method in interface org.apache.mahout.ep.Payload
 
update(String) - Method in class org.apache.mahout.fpm.pfpgrowth.convertors.ContextStatusUpdater
 
update(String) - Method in interface org.apache.mahout.fpm.pfpgrowth.convertors.StatusUpdater
 
updateCentroids(Iterable<Canopy>) - Static method in class org.apache.mahout.clustering.canopy.CanopyClusterer
Iterate through the canopies, resetting their center to their centroids
updateCluster(Cluster, int) - Method in class org.apache.mahout.clustering.dirichlet.DirichletClusterer
 
updateCounts - Variable in class org.apache.mahout.classifier.sgd.AbstractOnlineLogisticRegression
 
updateHdfsState() - Method in class org.apache.mahout.math.hadoop.decomposer.HdfsBackedLanczosState
 
updateItemPref(long, float) - Method in class org.apache.mahout.cf.taste.impl.recommender.slopeone.file.FileDiffStorage
 
updateItemPref(long, float) - Method in class org.apache.mahout.cf.taste.impl.recommender.slopeone.MemoryDiffStorage
 
updateItemPref(long, float) - Method in interface org.apache.mahout.cf.taste.recommender.slopeone.DiffStorage
Updates internal data structures to reflect an update in a preference value for an item.
updateLogProbGivenTopic(int, int, double) - Method in class org.apache.mahout.clustering.lda.LDAState
 
updateLogTotals(int, double) - Method in class org.apache.mahout.clustering.lda.LDAState
 
updateModels(Cluster[]) - Method in class org.apache.mahout.clustering.dirichlet.DirichletClusterer
 
updatePerLabelThetaNormalizer(int, double) - Method in class org.apache.mahout.classifier.naivebayes.training.AbstractThetaTrainer
 
updateRanking(Vector, Collection<Integer>, int, Random) - Method in class org.apache.mahout.classifier.sgd.GradientMachine
Updates using ranking loss.
updateSteps - Variable in class org.apache.mahout.classifier.sgd.AbstractOnlineLogisticRegression
 
updateTopic(int, Vector) - Method in class org.apache.mahout.clustering.lda.cvb.TopicModel
 
UpperTriangular - Class in org.apache.mahout.math.hadoop.stochasticsvd
Quick and dirty implementation of some Matrix methods over packed upper triangular matrix.
UpperTriangular(int) - Constructor for class org.apache.mahout.math.hadoop.stochasticsvd.UpperTriangular
represents n x n upper triangular matrix
UpperTriangular(double[], boolean) - Constructor for class org.apache.mahout.math.hadoop.stochasticsvd.UpperTriangular
 
UpperTriangular(Vector) - Constructor for class org.apache.mahout.math.hadoop.stochasticsvd.UpperTriangular
 
UpperTriangular(UpperTriangular) - Constructor for class org.apache.mahout.math.hadoop.stochasticsvd.UpperTriangular
 
USE_FPG2 - Static variable in class org.apache.mahout.fpm.pfpgrowth.PFPGrowth
 
USE_NAMED_VECTORS - Static variable in class org.apache.mahout.vectorizer.EncodingMapper
 
USE_SEQUENTIAL - Static variable in class org.apache.mahout.vectorizer.EncodingMapper
 
USER_VECTORS - Static variable in class org.apache.mahout.cf.taste.hadoop.preparation.PreparePreferenceMatrixJob
 
UserBasedRecommender - Interface in org.apache.mahout.cf.taste.recommender
Interface implemented by "user-based" recommenders.
UserIDsMapper - Class in org.apache.mahout.cf.taste.hadoop.pseudo
Extracts and emits all user IDs from the users file, or input file.
UserIDsMapper() - Constructor for class org.apache.mahout.cf.taste.hadoop.pseudo.UserIDsMapper
 
userIndex(long) - Method in class org.apache.mahout.cf.taste.impl.recommender.svd.AbstractFactorizer
 
UserNeighborhood - Interface in org.apache.mahout.cf.taste.neighborhood
Implementations of this interface compute a "neighborhood" of users like a given user.
userSimilarity(long, long) - Method in class org.apache.mahout.cf.taste.impl.similarity.CachingUserSimilarity
 
userSimilarity(long, long) - Method in class org.apache.mahout.cf.taste.impl.similarity.CityBlockSimilarity
 
userSimilarity(long, long) - Method in class org.apache.mahout.cf.taste.impl.similarity.GenericUserSimilarity
 
userSimilarity(long, long) - Method in class org.apache.mahout.cf.taste.impl.similarity.LogLikelihoodSimilarity
 
userSimilarity(long, long) - Method in class org.apache.mahout.cf.taste.impl.similarity.SpearmanCorrelationSimilarity
 
userSimilarity(long, long) - Method in class org.apache.mahout.cf.taste.impl.similarity.TanimotoCoefficientSimilarity
 
UserSimilarity - Interface in org.apache.mahout.cf.taste.similarity
Implementations of this interface define a notion of similarity between two users.
userSimilarity(long, long) - Method in interface org.apache.mahout.cf.taste.similarity.UserSimilarity
Returns the degree of similarity, of two users, based on the their preferences.
UserVectorSplitterMapper - Class in org.apache.mahout.cf.taste.hadoop.item
 
UserVectorSplitterMapper() - Constructor for class org.apache.mahout.cf.taste.hadoop.item.UserVectorSplitterMapper
 
usesFirstLineAsSchema() - Method in class org.apache.mahout.classifier.sgd.CsvRecordFactory
 
usesFirstLineAsSchema() - Method in interface org.apache.mahout.classifier.sgd.RecordFactory
 
useT3T4() - Method in class org.apache.mahout.clustering.canopy.CanopyClusterer
Used by CanopyReducer to set t1=t3 and t2=t4 configuration values

V

validate() - Method in class org.apache.mahout.classifier.naivebayes.NaiveBayesModel
 
validate(HmmModel) - Static method in class org.apache.mahout.classifier.sequencelearning.hmm.HmmUtils
Validates an HMM model set
validModel() - Method in class org.apache.mahout.classifier.sgd.AbstractOnlineLogisticRegression
 
validModel() - Method in class org.apache.mahout.classifier.sgd.CrossFoldLearner
 
value() - Method in class org.apache.mahout.math.stats.GlobalOnlineAuc
 
ValueCounterMapper - Class in org.apache.mahout.math.stats.entropy
Emits the value and the count of 1 as VarIntWritable.
ValueCounterMapper() - Constructor for class org.apache.mahout.math.stats.entropy.ValueCounterMapper
 
valueOf(String) - Static method in enum org.apache.mahout.cf.taste.common.Weighting
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.apache.mahout.cf.taste.hadoop.item.ToUserVectorsReducer.Counters
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.apache.mahout.cf.taste.hadoop.pseudo.ReducerMetrics
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.apache.mahout.classifier.df.data.Dataset.Attribute
Returns the enum constant of this type with the specified name.
valueOf(int, String) - Method in class org.apache.mahout.classifier.df.data.Dataset
Converts a token to its corresponding int code for a given attribute
valueOf(String) - Static method in enum org.apache.mahout.classifier.df.node.Node.Type
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.apache.mahout.classifier.naivebayes.training.IndexInstancesMapper.Counter
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.apache.mahout.clustering.lda.cvb.CachingCVB0PerplexityMapper.Counters
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.apache.mahout.clustering.minhash.HashFactory.HashType
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.apache.mahout.common.iterator.sequencefile.PathType
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.apache.mahout.math.hadoop.similarity.cooccurrence.measures.VectorSimilarityMeasures
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.apache.mahout.vectorizer.collocations.llr.CollocMapper.Count
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.apache.mahout.vectorizer.collocations.llr.CollocReducer.Skipped
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.apache.mahout.vectorizer.collocations.llr.Gram.Type
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.apache.mahout.vectorizer.collocations.llr.LLRReducer.Skipped
Returns the enum constant of this type with the specified name.
values() - Static method in enum org.apache.mahout.cf.taste.common.Weighting
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.apache.mahout.cf.taste.hadoop.item.ToUserVectorsReducer.Counters
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.apache.mahout.cf.taste.hadoop.pseudo.ReducerMetrics
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Method in class org.apache.mahout.cf.taste.impl.common.FastMap
 
values(int) - Method in class org.apache.mahout.classifier.df.data.Data
finds all distinct values of a given attribute
values() - Static method in enum org.apache.mahout.classifier.df.data.Dataset.Attribute
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.apache.mahout.classifier.df.node.Node.Type
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.apache.mahout.classifier.naivebayes.training.IndexInstancesMapper.Counter
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.apache.mahout.clustering.lda.cvb.CachingCVB0PerplexityMapper.Counters
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.apache.mahout.clustering.minhash.HashFactory.HashType
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.apache.mahout.common.iterator.sequencefile.PathType
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.apache.mahout.math.hadoop.similarity.cooccurrence.measures.VectorSimilarityMeasures
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.apache.mahout.vectorizer.collocations.llr.CollocMapper.Count
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.apache.mahout.vectorizer.collocations.llr.CollocReducer.Skipped
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.apache.mahout.vectorizer.collocations.llr.Gram.Type
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.apache.mahout.vectorizer.collocations.llr.LLRReducer.Skipped
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Method in class org.apache.mahout.vectorizer.encoders.Dictionary
 
variance(Path, Path, Configuration) - Static method in class org.apache.mahout.math.hadoop.stats.BasicStats
Calculate the variance of values stored as
varianceForGivenMean(Path, Path, double, Configuration) - Static method in class org.apache.mahout.math.hadoop.stats.BasicStats
Calculate the variance by a predefined mean of values stored as
VarianceTotals - Class in org.apache.mahout.math.hadoop.stats
Holds the total values needed to compute mean and standard deviation Provides methods for their computation
VarianceTotals() - Constructor for class org.apache.mahout.math.hadoop.stats.VarianceTotals
 
Varint - Class in org.apache.mahout.math
Encodes signed and unsigned values using a common variable-length scheme, found for example in Google's Protocol Buffers.
VarIntSumReducer - Class in org.apache.mahout.math.stats.entropy
The analog of org.apache.hadoop.mapreduce.lib.reduce.IntSumReducer which uses VarIntWritable.
VarIntSumReducer() - Constructor for class org.apache.mahout.math.stats.entropy.VarIntSumReducer
 
VarIntWritable - Class in org.apache.mahout.math
 
VarIntWritable() - Constructor for class org.apache.mahout.math.VarIntWritable
 
VarIntWritable(int) - Constructor for class org.apache.mahout.math.VarIntWritable
 
VarLongWritable - Class in org.apache.mahout.math
 
VarLongWritable() - Constructor for class org.apache.mahout.math.VarLongWritable
 
VarLongWritable(long) - Constructor for class org.apache.mahout.math.VarLongWritable
 
VECTOR_CACHE_BASE - Static variable in interface org.apache.mahout.clustering.spectral.eigencuts.EigencutsKeys
Base path to the location on HDFS where the diagonal matrix (a vector) and the list of eigenvalues will be stored for one of the map/reduce jobs in Eigencuts.
VECTOR_COUNT - Static variable in class org.apache.mahout.vectorizer.tfidf.TFIDFConverter
 
VectorAndPrefsWritable - Class in org.apache.mahout.cf.taste.hadoop.item
 
VectorAndPrefsWritable() - Constructor for class org.apache.mahout.cf.taste.hadoop.item.VectorAndPrefsWritable
 
VectorAndPrefsWritable(Vector, List<Long>, List<Float>) - Constructor for class org.apache.mahout.cf.taste.hadoop.item.VectorAndPrefsWritable
 
VectorCache - Class in org.apache.mahout.clustering.spectral.common
This class handles reading and writing vectors to the Hadoop distributed cache.
VectorDistanceInvertedMapper - Class in org.apache.mahout.math.hadoop.similarity
Similar to VectorDistanceMapper, except it outputs <input, Vector>, where the vector is a dense vector contain one entry for every seed vector
VectorDistanceInvertedMapper() - Constructor for class org.apache.mahout.math.hadoop.similarity.VectorDistanceInvertedMapper
 
VectorDistanceMapper - Class in org.apache.mahout.math.hadoop.similarity
 
VectorDistanceMapper() - Constructor for class org.apache.mahout.math.hadoop.similarity.VectorDistanceMapper
 
VectorDistanceSimilarityJob - Class in org.apache.mahout.math.hadoop.similarity
This class does a Map-side join between seed vectors (the map side can also be a Cluster) and a list of other vectors and emits the a tuple of seed id, other id, distance.
VectorDistanceSimilarityJob() - Constructor for class org.apache.mahout.math.hadoop.similarity.VectorDistanceSimilarityJob
 
Vectorizer - Interface in org.apache.mahout.vectorizer
 
VectorizerConfig - Class in org.apache.mahout.vectorizer
The config for a Vectorizer.
VectorizerConfig(Configuration, String, String, String, boolean, boolean, int) - Constructor for class org.apache.mahout.vectorizer.VectorizerConfig
 
VectorMatrixMultiplicationJob - Class in org.apache.mahout.clustering.spectral.common
This class handles the three-way multiplication of the digonal matrix and the Markov transition matrix inherent in the Eigencuts algorithm.
VectorMatrixMultiplicationJob.VectorMatrixMultiplicationMapper - Class in org.apache.mahout.clustering.spectral.common
 
VectorMatrixMultiplicationJob.VectorMatrixMultiplicationMapper() - Constructor for class org.apache.mahout.clustering.spectral.common.VectorMatrixMultiplicationJob.VectorMatrixMultiplicationMapper
 
VectorOrPrefWritable - Class in org.apache.mahout.cf.taste.hadoop.item
 
VectorOrPrefWritable() - Constructor for class org.apache.mahout.cf.taste.hadoop.item.VectorOrPrefWritable
 
VectorOrPrefWritable(Vector) - Constructor for class org.apache.mahout.cf.taste.hadoop.item.VectorOrPrefWritable
 
VectorOrPrefWritable(long, float) - Constructor for class org.apache.mahout.cf.taste.hadoop.item.VectorOrPrefWritable
 
Vectors - Class in org.apache.mahout.math.hadoop.similarity.cooccurrence
 
VectorSimilarityMeasure - Interface in org.apache.mahout.math.hadoop.similarity.cooccurrence.measures
 
VectorSimilarityMeasures - Enum in org.apache.mahout.math.hadoop.similarity.cooccurrence.measures
 
VectorSumReducer - Class in org.apache.mahout.common.mapreduce
 
VectorSumReducer() - Constructor for class org.apache.mahout.common.mapreduce.VectorSumReducer
 
vectorToSortedString(Vector, String[]) - Static method in class org.apache.mahout.clustering.lda.cvb.TopicModel
 
VectorWritable - Class in org.apache.mahout.math
 
VectorWritable() - Constructor for class org.apache.mahout.math.VectorWritable
 
VectorWritable(Vector) - Constructor for class org.apache.mahout.math.VectorWritable
 
VectorWritable(Vector, boolean) - Constructor for class org.apache.mahout.math.VectorWritable
 
Version - Class in org.apache.mahout
 
version() - Static method in class org.apache.mahout.Version
 
versionFromResource() - Static method in class org.apache.mahout.Version
 
VERTEX_INDEX - Static variable in class org.apache.mahout.graph.AdjacencyMatrixJob
 
VertexWritable - Class in org.apache.mahout.clustering.spectral.common
Represents a vertex within the affinity graph for Eigencuts.
VertexWritable() - Constructor for class org.apache.mahout.clustering.spectral.common.VertexWritable
 
VertexWritable(int, int, double, String) - Constructor for class org.apache.mahout.clustering.spectral.common.VertexWritable
 
viewPart(int[], int[]) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.UpperTriangular
 
viterbiAlgorithm(HmmModel, int[], boolean) - Static method in class org.apache.mahout.classifier.sequencelearning.hmm.HmmAlgorithms
Viterbi algorithm to compute the most likely hidden sequence for a given model and observed sequence
ViterbiEvaluator - Class in org.apache.mahout.classifier.sequencelearning.hmm
Command-line tool for Viterbi evaluating
VJob - Class in org.apache.mahout.math.hadoop.stochasticsvd
 
VJob() - Constructor for class org.apache.mahout.math.hadoop.stochasticsvd.VJob
 
VJob.VMapper - Class in org.apache.mahout.math.hadoop.stochasticsvd
 
VJob.VMapper() - Constructor for class org.apache.mahout.math.hadoop.stochasticsvd.VJob.VMapper
 

W

waitForCompletion() - Method in class org.apache.mahout.math.hadoop.stochasticsvd.UJob
 
waitForCompletion() - Method in class org.apache.mahout.math.hadoop.stochasticsvd.VJob
 
WEIGHT - Static variable in class org.apache.mahout.classifier.bayes.mapreduce.common.BayesConstants
 
weight(int, int) - Method in class org.apache.mahout.classifier.naivebayes.NaiveBayesModel
 
weight(byte[]) - Method in class org.apache.mahout.vectorizer.encoders.AdaptiveWordValueEncoder
 
weight(byte[]) - Method in class org.apache.mahout.vectorizer.encoders.StaticWordValueEncoder
 
weight(byte[]) - Method in class org.apache.mahout.vectorizer.encoders.WordValueEncoder
 
Weight - Interface in org.apache.mahout.vectorizer
 
WeightedDistanceMeasure - Class in org.apache.mahout.common.distance
Abstract implementation of DistanceMeasure with support for weights.
WeightedDistanceMeasure() - Constructor for class org.apache.mahout.common.distance.WeightedDistanceMeasure
 
WeightedEuclideanDistanceMeasure - Class in org.apache.mahout.common.distance
This class implements a Euclidean distance metric by summing the square root of the squared differences between each coordinate, optionally adding weights.
WeightedEuclideanDistanceMeasure() - Constructor for class org.apache.mahout.common.distance.WeightedEuclideanDistanceMeasure
 
WeightedManhattanDistanceMeasure - Class in org.apache.mahout.common.distance
This class implements a "Manhattan distance" metric by summing the absolute values of the difference between each coordinate, optionally with weights.
WeightedManhattanDistanceMeasure() - Constructor for class org.apache.mahout.common.distance.WeightedManhattanDistanceMeasure
 
WeightedPropertyVectorWritable - Class in org.apache.mahout.clustering
 
WeightedPropertyVectorWritable() - Constructor for class org.apache.mahout.clustering.WeightedPropertyVectorWritable
 
WeightedPropertyVectorWritable(Map<Text, Text>) - Constructor for class org.apache.mahout.clustering.WeightedPropertyVectorWritable
 
WeightedPropertyVectorWritable(double, Vector, Map<Text, Text>) - Constructor for class org.apache.mahout.clustering.WeightedPropertyVectorWritable
 
WeightedRunningAverage - Class in org.apache.mahout.cf.taste.impl.common
 
WeightedRunningAverage() - Constructor for class org.apache.mahout.cf.taste.impl.common.WeightedRunningAverage
 
WeightedRunningAverageAndStdDev - Class in org.apache.mahout.cf.taste.impl.common
This subclass also provides for a weighted estimate of the sample standard deviation.
WeightedRunningAverageAndStdDev() - Constructor for class org.apache.mahout.cf.taste.impl.common.WeightedRunningAverageAndStdDev
 
WeightedVectorWritable - Class in org.apache.mahout.clustering
 
WeightedVectorWritable() - Constructor for class org.apache.mahout.clustering.WeightedVectorWritable
 
WeightedVectorWritable(double, Vector) - Constructor for class org.apache.mahout.clustering.WeightedVectorWritable
 
Weighting - Enum in org.apache.mahout.cf.taste.common
A simple enum which gives symbolic names to the ideas of "weighted" and "unweighted", to make various API calls which take a weighting parameter more readable.
WEIGHTS - Static variable in class org.apache.mahout.classifier.naivebayes.training.TrainNaiveBayesJob
 
WEIGHTS_PER_FEATURE - Static variable in class org.apache.mahout.classifier.naivebayes.training.TrainNaiveBayesJob
 
WEIGHTS_PER_LABEL - Static variable in class org.apache.mahout.classifier.naivebayes.training.TrainNaiveBayesJob
 
WeightsMapper - Class in org.apache.mahout.classifier.naivebayes.training
 
WeightsMapper() - Constructor for class org.apache.mahout.classifier.naivebayes.training.WeightsMapper
 
WinnowTrainer - Class in org.apache.mahout.classifier.discriminative
This class implements training according to the winnow update algorithm.
WinnowTrainer(int, double, double, double, double) - Constructor for class org.apache.mahout.classifier.discriminative.WinnowTrainer
 
WinnowTrainer(int, double) - Constructor for class org.apache.mahout.classifier.discriminative.WinnowTrainer
 
WinnowTrainer(int) - Constructor for class org.apache.mahout.classifier.discriminative.WinnowTrainer
Initializes with dimension and promotionStep of 2.
WORD_LIKE_VALUE_HASH_SEED - Static variable in class org.apache.mahout.vectorizer.encoders.FeatureVectorEncoder
 
WORDCOUNT_OUTPUT_FOLDER - Static variable in class org.apache.mahout.vectorizer.tfidf.TFIDFConverter
 
WordsPrunerReducer - Class in org.apache.mahout.vectorizer.pruner
 
WordsPrunerReducer() - Constructor for class org.apache.mahout.vectorizer.pruner.WordsPrunerReducer
 
WordValueEncoder - Class in org.apache.mahout.vectorizer.encoders
Encodes words as sparse vector updates to a Vector.
WordValueEncoder(String) - Constructor for class org.apache.mahout.vectorizer.encoders.WordValueEncoder
 
WRITABLE_VERSION - Static variable in class org.apache.mahout.classifier.sgd.GradientMachine
 
WRITABLE_VERSION - Static variable in class org.apache.mahout.classifier.sgd.OnlineLogisticRegression
 
WRITABLE_VERSION - Static variable in class org.apache.mahout.classifier.sgd.PassiveAggressive
 
write(DataOutput) - Method in class org.apache.mahout.cf.taste.hadoop.EntityCountWritable
 
write(DataOutput) - Method in class org.apache.mahout.cf.taste.hadoop.EntityEntityWritable
 
write(DataOutput) - Method in class org.apache.mahout.cf.taste.hadoop.EntityPrefWritable
 
write(DataOutput) - Method in class org.apache.mahout.cf.taste.hadoop.item.PrefAndSimilarityColumnWritable
 
write(DataOutput) - Method in class org.apache.mahout.cf.taste.hadoop.item.VectorAndPrefsWritable
 
write(DataOutput) - Method in class org.apache.mahout.cf.taste.hadoop.item.VectorOrPrefWritable
 
write(DataOutput) - Method in class org.apache.mahout.cf.taste.hadoop.RecommendedItemsWritable
 
write(DataOutput) - Method in class org.apache.mahout.cf.taste.hadoop.slopeone.FullRunningAverageAndStdDevWritable
 
write(DataOutput) - Method in class org.apache.mahout.classifier.df.data.Dataset
 
write(DataOutput) - Method in class org.apache.mahout.classifier.df.DecisionForest
 
write(DataOutput) - Method in class org.apache.mahout.classifier.df.mapreduce.inmem.InMemInputFormat.InMemInputSplit
 
write(DataOutput) - Method in class org.apache.mahout.classifier.df.mapreduce.MapredOutput
 
write(DataOutput) - Method in class org.apache.mahout.classifier.df.node.Node
 
write(DataOutput) - Method in class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression.TrainingExample
 
write(DataOutput) - Method in class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression.Wrapper
 
write(DataOutput) - Method in class org.apache.mahout.classifier.sgd.AdaptiveLogisticRegression
 
write(DataOutput) - Method in class org.apache.mahout.classifier.sgd.CrossFoldLearner
 
write(DataOutput) - Method in class org.apache.mahout.classifier.sgd.ElasticBandPrior
 
write(DataOutput) - Method in class org.apache.mahout.classifier.sgd.GradientMachine
 
write(DataOutput) - Method in class org.apache.mahout.classifier.sgd.L1
 
write(DataOutput) - Method in class org.apache.mahout.classifier.sgd.L2
 
write(DataOutput) - Method in class org.apache.mahout.classifier.sgd.OnlineLogisticRegression
 
write(DataOutput) - Method in class org.apache.mahout.classifier.sgd.PassiveAggressive
 
write(DataOutput, T) - Static method in class org.apache.mahout.classifier.sgd.PolymorphicWritable
 
write(DataOutput) - Method in class org.apache.mahout.classifier.sgd.TPrior
 
write(DataOutput) - Method in class org.apache.mahout.classifier.sgd.UniformPrior
 
write(DataOutput) - Method in class org.apache.mahout.clustering.AbstractCluster
 
write(DataOutput) - Method in class org.apache.mahout.clustering.ClusterClassifier
 
write(DataOutput) - Method in class org.apache.mahout.clustering.ClusterObservations
 
write(DataOutput) - Method in class org.apache.mahout.clustering.dirichlet.DirichletCluster
 
write(DataOutput) - Method in class org.apache.mahout.clustering.DistanceMeasureCluster
 
write(DataOutput) - Method in class org.apache.mahout.clustering.kmeans.Cluster
 
write(DataOutput) - Method in class org.apache.mahout.clustering.meanshift.MeanShiftCanopy
 
write(DataOutput) - Method in class org.apache.mahout.clustering.spectral.common.IntDoublePairWritable
 
write(DataOutput) - Method in class org.apache.mahout.clustering.spectral.common.VertexWritable
 
write(DataOutput) - Method in class org.apache.mahout.clustering.spectral.eigencuts.EigencutsSensitivityNode
 
write(DataOutput) - Method in class org.apache.mahout.clustering.WeightedPropertyVectorWritable
 
write(DataOutput) - Method in class org.apache.mahout.clustering.WeightedVectorWritable
 
write(DataOutput) - Method in class org.apache.mahout.common.IntegerTuple
 
write(DataOutput) - Method in class org.apache.mahout.common.IntPairWritable
 
write(DataOutput) - Method in class org.apache.mahout.common.IntTuple
 
write(DataOutput) - Method in class org.apache.mahout.common.StringTuple
 
write(DataOutput) - Method in class org.apache.mahout.ep.EvolutionaryProcess
 
write(DataOutput) - Method in class org.apache.mahout.ep.Mapping.Exponential
 
write(DataOutput) - Method in class org.apache.mahout.ep.Mapping.Identity
 
write(DataOutput) - Method in class org.apache.mahout.ep.Mapping.LogLimit
 
write(DataOutput) - Method in class org.apache.mahout.ep.Mapping.SoftLimit
 
write(DataOutput) - Method in class org.apache.mahout.ep.State
 
write(DataOutput) - Method in class org.apache.mahout.fpm.pfpgrowth.convertors.string.TopKStringPatterns
 
write(DataOutput) - Method in class org.apache.mahout.fpm.pfpgrowth.TransactionTree
 
write(Path, Configuration, Iterable<MatrixSlice>) - Static method in class org.apache.mahout.math.DistributedRowMatrixWriter
 
write(DataOutput) - Method in class org.apache.mahout.math.hadoop.DistributedRowMatrix.MatrixEntryWritable
 
write(Vector, Path, Configuration) - Static method in class org.apache.mahout.math.hadoop.similarity.cooccurrence.Vectors
 
write(Vector, Path, Configuration, boolean) - Static method in class org.apache.mahout.math.hadoop.similarity.cooccurrence.Vectors
 
write(DataOutput) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.DenseBlockWritable
 
write(DataOutput) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.SparseRowBlockWritable
 
write(DataOutput) - Method in class org.apache.mahout.math.hadoop.stochasticsvd.SplitPartitionedWritable
 
write(Path, Configuration, VectorIterable) - Static method in class org.apache.mahout.math.MatrixUtils
 
write(DataOutput) - Method in class org.apache.mahout.math.MatrixWritable
 
write(DataOutput) - Method in class org.apache.mahout.math.MultiLabelVectorWritable
 
write(DataOutput, SequentialAccessSparseVector, int[]) - Static method in class org.apache.mahout.math.MultiLabelVectorWritable
 
write(DataOutput) - Method in class org.apache.mahout.math.stats.GlobalOnlineAuc
 
write(DataOutput) - Method in class org.apache.mahout.math.stats.GroupedOnlineAuc
 
write(DataOutput) - Method in class org.apache.mahout.math.VarIntWritable
 
write(DataOutput) - Method in class org.apache.mahout.math.VarLongWritable
 
write(DataOutput) - Method in class org.apache.mahout.math.VectorWritable
 
write(DataOutput) - Method in class org.apache.mahout.vectorizer.collocations.llr.Gram
 
write(DataOutput) - Method in class org.apache.mahout.vectorizer.collocations.llr.GramKey
 
writeArray(DataOutput, Node[]) - Static method in class org.apache.mahout.classifier.df.DFUtils
Writes an Node[] into a DataOutput
writeArray(DataOutput, double[]) - Static method in class org.apache.mahout.classifier.df.DFUtils
Writes a double[] into a DataOutput
writeArray(DataOutput, int[]) - Static method in class org.apache.mahout.classifier.df.DFUtils
Writes an int[] into a DataOutput
writeBinary(Factorization, DataOutput) - Static method in class org.apache.mahout.cf.taste.impl.recommender.svd.FilePersistenceStrategy
 
writeBinary(String, CrossFoldLearner) - Static method in class org.apache.mahout.classifier.sgd.ModelSerializer
 
writeBinary(String, OnlineLogisticRegression) - Static method in class org.apache.mahout.classifier.sgd.ModelSerializer
 
writeBinary(String, AdaptiveLogisticRegression) - Static method in class org.apache.mahout.classifier.sgd.ModelSerializer
 
writeClassifier(ClusterClassifier, Path, String) - Static method in class org.apache.mahout.clustering.ClusterIterator
 
writeInt(int, Path, Configuration) - Static method in class org.apache.mahout.common.HadoopUtil
 
writeLabelBindings(DataOutput, Map<String, Integer>, Map<String, Integer>) - Static method in class org.apache.mahout.math.MatrixWritable
 
writeLabelIndex(Configuration, Iterable<String>, Path) - Static method in class org.apache.mahout.classifier.naivebayes.BayesUtils
Write the list of labels into a map file
writeLabelIndex(Configuration, Path, Iterable<Pair<Text, IntWritable>>) - Static method in class org.apache.mahout.classifier.naivebayes.BayesUtils
 
writeMatrix(DataOutput, Matrix) - Static method in class org.apache.mahout.math.MatrixWritable
Writes a typed Matrix instance to the output stream
writeModel(DataOutput, Model<?>) - Static method in class org.apache.mahout.clustering.dirichlet.DirichletCluster
Writes a typed Model instance to the output stream
writeModel(Path) - Method in class org.apache.mahout.clustering.lda.cvb.InMemoryCollapsedVariationalBayes0
 
writeNode(DataOutput) - Method in class org.apache.mahout.classifier.df.node.CategoricalNode
 
writeNode(DataOutput) - Method in class org.apache.mahout.classifier.df.node.Leaf
 
writeNode(DataOutput) - Method in class org.apache.mahout.classifier.df.node.Node
 
writeNode(DataOutput) - Method in class org.apache.mahout.classifier.df.node.NumericalNode
 
writeSignedVarInt(int, DataOutput) - Static method in class org.apache.mahout.math.Varint
 
writeSignedVarLong(long, DataOutput) - Static method in class org.apache.mahout.math.Varint
Encodes a value using the variable-length encoding from Google Protocol Buffers.
writeUnsignedVarInt(int, DataOutput) - Static method in class org.apache.mahout.math.Varint
 
writeUnsignedVarLong(long, DataOutput) - Static method in class org.apache.mahout.math.Varint
Encodes a value using the variable-length encoding from Google Protocol Buffers.
writeVector(DataOutput, Vector) - Static method in class org.apache.mahout.math.VectorWritable
Write the vector to the output
writeVector(DataOutput, Vector, boolean) - Static method in class org.apache.mahout.math.VectorWritable
 

Y

yiRow - Variable in class org.apache.mahout.math.hadoop.stochasticsvd.ABtDenseOutJob.QRReducer
 
YtYJob - Class in org.apache.mahout.math.hadoop.stochasticsvd
Job that accumulates Y'Y output
YtYJob.YtYMapper - Class in org.apache.mahout.math.hadoop.stochasticsvd
 
YtYJob.YtYMapper() - Constructor for class org.apache.mahout.math.hadoop.stochasticsvd.YtYJob.YtYMapper
 
YtYJob.YtYReducer - Class in org.apache.mahout.math.hadoop.stochasticsvd
 
YtYJob.YtYReducer() - Constructor for class org.apache.mahout.math.hadoop.stochasticsvd.YtYJob.YtYReducer
 

Z

ZScore - Class in org.apache.mahout.cf.taste.impl.transforms
Normalizes preference values for a user by converting them to "z-scores".
ZScore(DataModel) - Constructor for class org.apache.mahout.cf.taste.impl.transforms.ZScore
 

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