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Packages that use ModelDistribution | |
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org.apache.mahout.clustering | This package provides several clustering algorithm implementations. |
org.apache.mahout.clustering.dirichlet | |
org.apache.mahout.clustering.dirichlet.models |
Uses of ModelDistribution in org.apache.mahout.clustering |
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Methods in org.apache.mahout.clustering that return ModelDistribution | |
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ModelDistribution<?> |
JsonModelDistributionAdapter.deserialize(com.google.gson.JsonElement json,
java.lang.reflect.Type typeOfT,
com.google.gson.JsonDeserializationContext context)
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Methods in org.apache.mahout.clustering with parameters of type ModelDistribution | |
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com.google.gson.JsonElement |
JsonModelDistributionAdapter.serialize(ModelDistribution<?> src,
java.lang.reflect.Type typeOfSrc,
com.google.gson.JsonSerializationContext context)
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Uses of ModelDistribution in org.apache.mahout.clustering.dirichlet |
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Methods in org.apache.mahout.clustering.dirichlet that return ModelDistribution | |
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ModelDistribution<VectorWritable> |
DirichletState.getModelFactory()
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Methods in org.apache.mahout.clustering.dirichlet with parameters of type ModelDistribution | |
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static org.apache.hadoop.fs.Path |
DirichletDriver.buildClusters(org.apache.hadoop.conf.Configuration conf,
org.apache.hadoop.fs.Path input,
org.apache.hadoop.fs.Path output,
ModelDistribution<VectorWritable> modelDistribution,
int numClusters,
int maxIterations,
double alpha0,
boolean runSequential)
Iterate over the input vectors to produce cluster directories for each iteration |
static java.util.List<Cluster[]> |
DirichletClusterer.clusterPoints(java.util.List<VectorWritable> points,
ModelDistribution<VectorWritable> modelFactory,
double alpha0,
int numClusters,
int thin,
int burnin,
int numIterations)
Create a new instance on the sample data with the given additional parameters |
protected static DirichletState |
DirichletMapper.loadState(org.apache.hadoop.conf.Configuration conf,
java.lang.String statePath,
ModelDistribution<VectorWritable> modelDistribution,
double alpha,
int k)
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static void |
DirichletDriver.run(org.apache.hadoop.conf.Configuration conf,
org.apache.hadoop.fs.Path input,
org.apache.hadoop.fs.Path output,
ModelDistribution<VectorWritable> modelDistribution,
int numModels,
int maxIterations,
double alpha0,
boolean runClustering,
boolean emitMostLikely,
double threshold,
boolean runSequential)
Iterate over the input vectors to produce clusters and, if requested, use the results of the final iteration to cluster the input vectors. |
static void |
DirichletDriver.run(org.apache.hadoop.fs.Path input,
org.apache.hadoop.fs.Path output,
ModelDistribution<VectorWritable> modelDistribution,
int numClusters,
int maxIterations,
double alpha0,
boolean runClustering,
boolean emitMostLikely,
double threshold,
boolean runSequential)
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. |
void |
DirichletState.setModelFactory(ModelDistribution<VectorWritable> modelFactory)
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Constructors in org.apache.mahout.clustering.dirichlet with parameters of type ModelDistribution | |
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DirichletClusterer(java.util.List<VectorWritable> sampleData,
ModelDistribution<VectorWritable> modelFactory,
double alpha0,
int numClusters,
int thin,
int burnin)
Create a new instance on the sample data with the given additional parameters |
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DirichletState(ModelDistribution<VectorWritable> modelFactory,
int numClusters,
double alpha0)
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Uses of ModelDistribution in org.apache.mahout.clustering.dirichlet.models |
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Classes in org.apache.mahout.clustering.dirichlet.models that implement ModelDistribution | |
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class |
AbstractVectorModelDistribution
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class |
AsymmetricSampledNormalDistribution
An implementation of the ModelDistribution interface suitable for testing the DirichletCluster algorithm. |
class |
DistanceMeasureClusterDistribution
An implementation of the ModelDistribution interface suitable for testing the DirichletCluster algorithm. |
class |
GaussianClusterDistribution
An implementation of the ModelDistribution interface suitable for testing the DirichletCluster algorithm. |
class |
L1ModelDistribution
An implementation of the ModelDistribution interface suitable for testing the DirichletCluster algorithm. |
class |
NormalModelDistribution
An implementation of the ModelDistribution interface suitable for testing the DirichletCluster algorithm. |
class |
SampledNormalDistribution
An implementation of the ModelDistribution interface suitable for testing the DirichletCluster algorithm. |
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