gov.sandia.cognition.statistics.bayesian

Class DirichletProcessMixtureModel.DPMMCluster<ObservationType>

java.lang.Object

gov.sandia.cognition.util.AbstractCloneableSerializable

gov.sandia.cognition.learning.algorithm.clustering.cluster.DefaultCluster<ObservationType>

gov.sandia.cognition.statistics.bayesian.DirichletProcessMixtureModel.DPMMCluster<ObservationType>

Type Parameters:

ObservationType - Types of observations of the DPMM

All Implemented Interfaces:

Cluster<ObservationType>, CloneableSerializable, java.io.Serializable, java.lang.Cloneable

Enclosing class:

DirichletProcessMixtureModel<ObservationType>

public static class DirichletProcessMixtureModel.DPMMCluster<ObservationType>
extends DefaultCluster<ObservationType>

Cluster for a step in the DPMM

See Also:

Serialized Form

Field Summary

Fields inherited from class gov.sandia.cognition.learning.algorithm.clustering.cluster.DefaultCluster

DEFAULT_INDEX

Constructor Summary

Constructors

Constructor and Description
DPMMCluster(java.util.Collection<? extends ObservationType> assignedData, ProbabilityFunction<? super ObservationType> probabilityFunction) Creates a new instance of DPMMCluster

Method Summary

Modifier and Type	Method and Description
DirichletProcessMixtureModel.DPMMCluster<ObservationType>	clone() This makes public the clone method on the Object class and removes the exception that it throws.
ProbabilityFunction<? super ObservationType>	getProbabilityFunction() Getter for probabilityFunction
void	setProbabilityFunction(ProbabilityFunction<? super ObservationType> probabilityFunction) Setter for probabilityFunction

Methods inherited from class gov.sandia.cognition.learning.algorithm.clustering.cluster.DefaultCluster

getIndex, getMembers, setIndex

Methods inherited from class java.lang.Object

equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

DPMMCluster

public DPMMCluster(java.util.Collection<? extends ObservationType> assignedData,
                   ProbabilityFunction<? super ObservationType> probabilityFunction)

Creates a new instance of DPMMCluster

Parameters:

assignedData - Data assigned to the cluster

probabilityFunction - Probability function describing the assigned data

Method Detail

clone

public DirichletProcessMixtureModel.DPMMCluster<ObservationType> clone()

Description copied from class: AbstractCloneableSerializable

This makes public the clone method on the Object class and removes the exception that it throws. Its default behavior is to automatically create a clone of the exact type of object that the clone is called on and to copy all primitives but to keep all references, which means it is a shallow copy. Extensions of this class may want to override this method (but call super.clone() to implement a "smart copy". That is, to target the most common use case for creating a copy of the object. Because of the default behavior being a shallow copy, extending classes only need to handle fields that need to have a deeper copy (or those that need to be reset). Some of the methods in ObjectUtil may be helpful in implementing a custom clone method. Note: The contract of this method is that you must use super.clone() as the basis for your implementation.

Specified by:

clone in interface CloneableSerializable

Overrides:

clone in class DefaultCluster<ObservationType>

Returns:

A clone of this object.

getProbabilityFunction

public ProbabilityFunction<? super ObservationType> getProbabilityFunction()

Getter for probabilityFunction

Returns:

Probability function describing the assigned data

setProbabilityFunction

public void setProbabilityFunction(ProbabilityFunction<? super ObservationType> probabilityFunction)

Setter for probabilityFunction

Parameters:

probabilityFunction - Probability function describing the assigned data