moa.classifiers.multilabel.meta

Class MLOzaBagAdwin

java.lang.Object

moa.AbstractMOAObject

moa.options.AbstractOptionHandler

moa.classifiers.AbstractClassifier

moa.classifiers.meta.OzaBagAdwin

moa.classifiers.multilabel.meta.MLOzaBagAdwin

All Implemented Interfaces:

Serializable, Classifier, AWTRenderable, MOAObject, OptionHandler

public class MLOzaBagAdwin
extends OzaBagAdwin

MLOzaBagAdwin: Changes the way to compute accuracy as an input for Adwin

Version:

$Revision: 1 $

Author:

Jesse Read (jesse@tsc.uc3m.es)

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
protected int	m_L

Fields inherited from class moa.classifiers.meta.OzaBagAdwin

ADError, baseLearnerOption, ensemble, ensembleSizeOption

Fields inherited from class moa.classifiers.AbstractClassifier

classifierRandom, modelContext, randomSeed, randomSeedOption, trainingWeightSeenByModel

Fields inherited from class moa.options.AbstractOptionHandler

classOptionNamesToPreparedObjects, options

Constructor Summary

Constructors

Constructor and Description
MLOzaBagAdwin()

Method Summary

Methods

Modifier and Type	Method and Description
double[]	getVotesForInstance(weka.core.Instance x) Predicts the class memberships for a given instance.
void	setModelContext(InstancesHeader raw_header) Sets the reference to the header of the data stream.
void	trainOnInstanceImpl(weka.core.Instance inst) Trains this classifier incrementally using the given instance. The reason for ...Impl methods: ease programmer burden by not requiring them to remember calls to super in overridden methods.

Methods inherited from class moa.classifiers.meta.OzaBagAdwin

getModelDescription, getModelMeasurementsImpl, getPurposeString, getSubClassifiers, isRandomizable, resetLearningImpl

Methods inherited from class moa.classifiers.AbstractClassifier

contextIsCompatible, copy, correctlyClassifies, getAttributeNameString, getAWTRenderer, getClassLabelString, getClassNameString, getDescription, getModelContext, getModelMeasurements, getNominalValueString, modelAttIndexToInstanceAttIndex, modelAttIndexToInstanceAttIndex, prepareForUseImpl, resetLearning, setRandomSeed, trainingHasStarted, trainingWeightSeenByModel, trainOnInstance

Methods inherited from class moa.options.AbstractOptionHandler

discoverOptionsViaReflection, getCLICreationString, getOptions, getPreparedClassOption, getPreparedClassOption, prepareClassOptions, prepareForUse, prepareForUse

Methods inherited from class moa.AbstractMOAObject

copy, measureByteSize, measureByteSize, toString

Methods inherited from class java.lang.Object

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

Methods inherited from interface moa.options.OptionHandler

getCLICreationString, getOptions, prepareForUse, prepareForUse

Methods inherited from interface moa.MOAObject

measureByteSize

Field Detail

m_L

protected int m_L

Constructor Detail

MLOzaBagAdwin

public MLOzaBagAdwin()

Method Detail

setModelContext

public void setModelContext(InstancesHeader raw_header)

Description copied from interface: Classifier

Sets the reference to the header of the data stream. The header of the data stream is extended from WEKA Instances. This header is needed to know the number of classes and attributes

Specified by:

setModelContext in interface Classifier

Overrides:

setModelContext in class AbstractClassifier

Parameters:

raw_header - the reference to the data stream header

trainOnInstanceImpl

public void trainOnInstanceImpl(weka.core.Instance inst)

Description copied from class: AbstractClassifier

Trains this classifier incrementally using the given instance.

The reason for ...Impl methods: ease programmer burden by not requiring them to remember calls to super in overridden methods. Note that this will produce compiler errors if not overridden.

Overrides:

trainOnInstanceImpl in class OzaBagAdwin

Parameters:

inst - the instance to be used for training

getVotesForInstance

public double[] getVotesForInstance(weka.core.Instance x)

Description copied from interface: Classifier

Predicts the class memberships for a given instance. If an instance is unclassified, the returned array elements must be all zero.

Specified by:

getVotesForInstance in interface Classifier

Overrides:

getVotesForInstance in class OzaBagAdwin

Parameters:

x - the instance to be classified

Returns:

an array containing the estimated membership probabilities of the test instance in each class