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.
 



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