## Uses of Interface
org.apache.mahout.clustering.ModelDistribution

Packages that use ModelDistribution
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

Methods in org.apache.mahout.clustering that return ModelDistribution
`ModelDistribution<?>` `JsonModelDistributionAdapter.deserialize(com.google.gson.JsonElement json, java.lang.reflect.Type typeOfT, com.google.gson.JsonDeserializationContext context)`

Methods in org.apache.mahout.clustering with parameters of type ModelDistribution
`com.google.gson.JsonElement` `JsonModelDistributionAdapter.serialize(ModelDistribution<?> src, java.lang.reflect.Type typeOfSrc, com.google.gson.JsonSerializationContext context)`

Uses of ModelDistribution in org.apache.mahout.clustering.dirichlet

Methods in org.apache.mahout.clustering.dirichlet that return ModelDistribution
`ModelDistribution<VectorWritable>` `DirichletState.getModelFactory()`

Methods in org.apache.mahout.clustering.dirichlet with parameters of type ModelDistribution
`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)`

`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)`

Constructors in org.apache.mahout.clustering.dirichlet with parameters of type ModelDistribution
`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
`DirichletState(ModelDistribution<VectorWritable> modelFactory, int numClusters, double alpha0)`

Uses of ModelDistribution in org.apache.mahout.clustering.dirichlet.models

Classes in org.apache.mahout.clustering.dirichlet.models that implement ModelDistribution
`class` `AbstractVectorModelDistribution`
`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.

Copyright © 2008-2010 The Apache Software Foundation. All Rights Reserved.