Mahout Core 0.4 API

Packages
org.apache.mahout.cf.taste.common  
org.apache.mahout.cf.taste.eval  
org.apache.mahout.cf.taste.hadoop  
org.apache.mahout.cf.taste.hadoop.item  
org.apache.mahout.cf.taste.hadoop.pseudo  
org.apache.mahout.cf.taste.hadoop.similarity.item  
org.apache.mahout.cf.taste.hadoop.slopeone  
org.apache.mahout.cf.taste.impl.common  
org.apache.mahout.cf.taste.impl.common.jdbc  
org.apache.mahout.cf.taste.impl.eval  
org.apache.mahout.cf.taste.impl.model  
org.apache.mahout.cf.taste.impl.model.file  
org.apache.mahout.cf.taste.impl.model.jdbc  
org.apache.mahout.cf.taste.impl.neighborhood  
org.apache.mahout.cf.taste.impl.recommender  
org.apache.mahout.cf.taste.impl.recommender.knn  
org.apache.mahout.cf.taste.impl.recommender.slopeone  
org.apache.mahout.cf.taste.impl.recommender.slopeone.file  
org.apache.mahout.cf.taste.impl.recommender.slopeone.jdbc  
org.apache.mahout.cf.taste.impl.recommender.svd  
org.apache.mahout.cf.taste.impl.similarity  
org.apache.mahout.cf.taste.impl.similarity.file  
org.apache.mahout.cf.taste.impl.similarity.jdbc  
org.apache.mahout.cf.taste.impl.transforms  
org.apache.mahout.cf.taste.model  
org.apache.mahout.cf.taste.neighborhood  
org.apache.mahout.cf.taste.recommender  
org.apache.mahout.cf.taste.recommender.slopeone  
org.apache.mahout.cf.taste.similarity  
org.apache.mahout.cf.taste.transforms  
org.apache.mahout.classifier  
org.apache.mahout.classifier.bayes
org.apache.mahout.classifier.bayes.algorithm  
org.apache.mahout.classifier.bayes.common  
org.apache.mahout.classifier.bayes.datastore  
org.apache.mahout.classifier.bayes.exceptions  
org.apache.mahout.classifier.bayes.interfaces  
org.apache.mahout.classifier.bayes.io  
org.apache.mahout.classifier.bayes.mapreduce.bayes  
org.apache.mahout.classifier.bayes.mapreduce.cbayes  
org.apache.mahout.classifier.bayes.mapreduce.common  
org.apache.mahout.classifier.bayes.model  
org.apache.mahout.classifier.discriminative  
org.apache.mahout.classifier.evaluation  
org.apache.mahout.classifier.naivebayes  
org.apache.mahout.classifier.naivebayes.trainer  
org.apache.mahout.classifier.sequencelearning.hmm  
org.apache.mahout.classifier.sgd Implements a variety of on-line logistric regression classifiers using SGD-based algorithms.
org.apache.mahout.clustering This package provides several clustering algorithm implementations.
org.apache.mahout.clustering.canopy  
org.apache.mahout.clustering.dirichlet  
org.apache.mahout.clustering.dirichlet.models  
org.apache.mahout.clustering.fuzzykmeans  
org.apache.mahout.clustering.kmeans This package provides an implementation of the k-means clustering algorithm.
org.apache.mahout.clustering.lda  
org.apache.mahout.clustering.meanshift  
org.apache.mahout.clustering.minhash  
org.apache.mahout.clustering.spectral.common  
org.apache.mahout.clustering.spectral.eigencuts  
org.apache.mahout.clustering.spectral.kmeans  
org.apache.mahout.common  
org.apache.mahout.common.cache  
org.apache.mahout.common.commandline  
org.apache.mahout.common.distance  
org.apache.mahout.common.iterator  
org.apache.mahout.common.nlp  
org.apache.mahout.common.parameters  
org.apache.mahout.df  
org.apache.mahout.df.builder  
org.apache.mahout.df.callback  
org.apache.mahout.df.data  
org.apache.mahout.df.data.conditions  
org.apache.mahout.df.mapreduce  
org.apache.mahout.df.mapreduce.inmem
In-memory mapreduce implementation of Random Decision Forests
 
Each mapper is responsible for growing a number of trees with a whole copy of the dataset loaded in memory, it uses the reference implementation's code to build each tree and estimate the oob error.

The dataset is distributed to the slave nodes using the DistributedCache.
org.apache.mahout.df.mapreduce.partial
Partial-data mapreduce implementation of Random Decision Forests
 
The builder splits the data, using a FileInputSplit, among the mappers.
org.apache.mahout.df.node  
org.apache.mahout.df.ref  
org.apache.mahout.df.split  
org.apache.mahout.df.tools  
org.apache.mahout.driver  
org.apache.mahout.ep Provides basic evolutionary optimization using recorded-step mutation.
org.apache.mahout.fpm.pfpgrowth
Map/Reduce(Parallel) implementation of FP Growth Algorithm for frequent Itemset Mining
 
We have a Top K Parallel FPGrowth Implementation.
org.apache.mahout.fpm.pfpgrowth.convertors  
org.apache.mahout.fpm.pfpgrowth.convertors.integer  
org.apache.mahout.fpm.pfpgrowth.convertors.string  
org.apache.mahout.fpm.pfpgrowth.fpgrowth  
org.apache.mahout.ga.watchmaker  
org.apache.mahout.math  
org.apache.mahout.math.hadoop  
org.apache.mahout.math.hadoop.decomposer  
org.apache.mahout.math.hadoop.similarity  
org.apache.mahout.math.hadoop.similarity.vector  
org.apache.mahout.math.stats  
org.apache.mahout.vectorizer  
org.apache.mahout.vectorizer.collocations.llr  
org.apache.mahout.vectorizer.common  
org.apache.mahout.vectorizer.document  
org.apache.mahout.vectorizer.encoders  
org.apache.mahout.vectorizer.term  
org.apache.mahout.vectorizer.tfidf  

 



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