org.apache.mahout.clustering.dirichlet.models
Class AsymmetricSampledNormalDistribution

java.lang.Object
  extended by org.apache.mahout.clustering.dirichlet.models.VectorModelDistribution
      extended by org.apache.mahout.clustering.dirichlet.models.AsymmetricSampledNormalDistribution
All Implemented Interfaces:
ModelDistribution<VectorWritable>

public class AsymmetricSampledNormalDistribution
extends VectorModelDistribution

An implementation of the ModelDistribution interface suitable for testing the DirichletCluster algorithm. Uses a Normal Distribution to sample the prior model values. Model values have a vector standard deviation, allowing assymetrical regions to be covered by a model.


Constructor Summary
AsymmetricSampledNormalDistribution()
           
AsymmetricSampledNormalDistribution(VectorWritable modelPrototype)
           
 
Method Summary
 Model<VectorWritable>[] sampleFromPosterior(Model<VectorWritable>[] posterior)
          Return a list of models sampled from the posterior
 Model<VectorWritable>[] sampleFromPrior(int howMany)
          Return a list of models sampled from the prior
 
Methods inherited from class org.apache.mahout.clustering.dirichlet.models.VectorModelDistribution
getModelPrototype, setModelPrototype
 
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 

Constructor Detail

AsymmetricSampledNormalDistribution

public AsymmetricSampledNormalDistribution()

AsymmetricSampledNormalDistribution

public AsymmetricSampledNormalDistribution(VectorWritable modelPrototype)
Method Detail

sampleFromPrior

public Model<VectorWritable>[] sampleFromPrior(int howMany)
Description copied from interface: ModelDistribution
Return a list of models sampled from the prior

Parameters:
howMany - the int number of models to return
Returns:
a Model[] representing what is known apriori

sampleFromPosterior

public Model<VectorWritable>[] sampleFromPosterior(Model<VectorWritable>[] posterior)
Description copied from interface: ModelDistribution
Return a list of models sampled from the posterior

Parameters:
posterior - the Model[] after observations
Returns:
a Model[] representing what is known apriori


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