org.apache.mahout.clustering.dirichlet.models
Class AsymmetricSampledNormalDistribution
java.lang.Object
org.apache.mahout.clustering.dirichlet.models.VectorModelDistribution
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.
Methods inherited from class java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
AsymmetricSampledNormalDistribution
public AsymmetricSampledNormalDistribution()
AsymmetricSampledNormalDistribution
public AsymmetricSampledNormalDistribution(VectorWritable modelPrototype)
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
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