gov.sandia.cognition.statistics.distribution

Class MixtureOfGaussians.Learner

java.lang.Object

gov.sandia.cognition.util.AbstractCloneableSerializable

gov.sandia.cognition.algorithm.AbstractIterativeAlgorithm

gov.sandia.cognition.algorithm.AnytimeAlgorithmWrapper<MixtureOfGaussians.PDF,KMeansClusterer<Vector,GaussianCluster>>

gov.sandia.cognition.statistics.distribution.MixtureOfGaussians.Learner

All Implemented Interfaces:

AnytimeAlgorithm<MixtureOfGaussians.PDF>, IterativeAlgorithm, IterativeAlgorithmListener, MeasurablePerformanceAlgorithm, StoppableAlgorithm, BatchLearner<java.util.Collection<? extends Vector>,MixtureOfGaussians.PDF>, DistributionEstimator<Vector,MixtureOfGaussians.PDF>, CloneableSerializable, java.io.Serializable, java.lang.Cloneable

Enclosing class:

MixtureOfGaussians

public static class MixtureOfGaussians.Learner
extends AnytimeAlgorithmWrapper<MixtureOfGaussians.PDF,KMeansClusterer<Vector,GaussianCluster>>
implements DistributionEstimator<Vector,MixtureOfGaussians.PDF>, MeasurablePerformanceAlgorithm

A hard-assignment learner for a MixtureOfGaussians

See Also:

Serialized Form

Field Summary

Fields inherited from class gov.sandia.cognition.algorithm.AbstractIterativeAlgorithm

DEFAULT_ITERATION, iteration

Constructor Summary

Constructors

Constructor and Description
Learner(KMeansClusterer<Vector,GaussianCluster> algorithm) Creates a new Learner

Method Summary

Modifier and Type	Method and Description
NamedValue<? extends java.lang.Number>	getPerformance() Gets the name-value pair that describes the current performance of the algorithm.
MixtureOfGaussians.PDF	getResult() Gets the current result of the algorithm.
MixtureOfGaussians.PDF	learn(java.util.Collection<? extends Vector> data) The learn method creates an object of ResultType using data of type DataType, using some form of "learning" algorithm.

Methods inherited from class gov.sandia.cognition.algorithm.AnytimeAlgorithmWrapper

algorithmEnded, algorithmStarted, clone, getAlgorithm, getIteration, getMaxIterations, isResultValid, readResolve, setAlgorithm, setMaxIterations, stepEnded, stepStarted, stop

Methods inherited from class gov.sandia.cognition.algorithm.AbstractIterativeAlgorithm

addIterativeAlgorithmListener, fireAlgorithmEnded, fireAlgorithmStarted, fireStepEnded, fireStepStarted, getListeners, removeIterativeAlgorithmListener, setIteration, setListeners

Methods inherited from class java.lang.Object

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

Methods inherited from interface gov.sandia.cognition.util.CloneableSerializable

clone

Methods inherited from interface gov.sandia.cognition.algorithm.IterativeAlgorithm

addIterativeAlgorithmListener, removeIterativeAlgorithmListener

Constructor Detail

Learner

public Learner(KMeansClusterer<Vector,GaussianCluster> algorithm)

Creates a new Learner

Parameters:

algorithm - KMeansClusterer to wrap.

Method Detail

getResult

public MixtureOfGaussians.PDF getResult()

Description copied from interface: AnytimeAlgorithm

Gets the current result of the algorithm.

Specified by:

getResult in interface AnytimeAlgorithm<MixtureOfGaussians.PDF>

Returns:

Current result of the algorithm.

learn

public MixtureOfGaussians.PDF learn(java.util.Collection<? extends Vector> data)

Description copied from interface: BatchLearner

The learn method creates an object of ResultType using data of type DataType, using some form of "learning" algorithm.

Specified by:

learn in interface BatchLearner<java.util.Collection<? extends Vector>,MixtureOfGaussians.PDF>

Parameters:

data - The data that the learning algorithm will use to create an object of ResultType.

Returns:

The object that is created based on the given data using the learning algorithm.

getPerformance

public NamedValue<? extends java.lang.Number> getPerformance()

Description copied from interface: MeasurablePerformanceAlgorithm

Gets the name-value pair that describes the current performance of the algorithm. For most algorithms, this is the value that they are attempting to optimize.

Specified by:

getPerformance in interface MeasurablePerformanceAlgorithm

Returns:

The name-value pair that describes the current performance of the algorithm.