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

java.lang.Object
  extended by gov.sandia.cognition.util.AbstractCloneableSerializable
      extended by gov.sandia.cognition.algorithm.AbstractIterativeAlgorithm
          extended by gov.sandia.cognition.algorithm.AnytimeAlgorithmWrapper<MixtureOfGaussians.PDF,KMeansClusterer<Vector,GaussianCluster>>
              extended by gov.sandia.cognition.statistics.distribution.MixtureOfGaussians.Learner
All Implemented Interfaces:
AnytimeAlgorithm<MixtureOfGaussians.PDF>, IterativeAlgorithm, IterativeAlgorithmListener, MeasurablePerformanceAlgorithm, StoppableAlgorithm, BatchLearner<Collection<? extends Vector>,MixtureOfGaussians.PDF>, DistributionEstimator<Vector,MixtureOfGaussians.PDF>, CloneableSerializable, Serializable, 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
MixtureOfGaussians.Learner(KMeansClusterer<Vector,GaussianCluster> algorithm)
          Creates a new Learner
 
Method Summary
 NamedValue<? extends 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(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

MixtureOfGaussians.Learner

public MixtureOfGaussians.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(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<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 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.