moa.classifiers.multilabel.meta

Class MLOzaBag

java.lang.Object

moa.AbstractMOAObject

moa.options.AbstractOptionHandler

moa.classifiers.AbstractClassifier

moa.classifiers.meta.OzaBag

moa.classifiers.multilabel.meta.MLOzaBag

All Implemented Interfaces:

Serializable, Classifier, AWTRenderable, MOAObject, OptionHandler

public class MLOzaBag
extends OzaBag

OzaBag for Multi-label data.

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.OzaBag

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
MLOzaBag()

Method Summary

Methods

Modifier and Type	Method and Description
double[]	getVotesForInstance(weka.core.Instance x) Predicts the class memberships for a given instance.
boolean	isRandomizable() Gets whether this classifier needs a random seed.
void	resetLearningImpl() Resets this classifier.
void	setModelContext(InstancesHeader raw_header) Sets the reference to the header of the data stream.

Methods inherited from class moa.classifiers.meta.OzaBag

getModelDescription, getModelMeasurementsImpl, getPurposeString, getSubClassifiers, trainOnInstanceImpl

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

MLOzaBag

public MLOzaBag()

Method Detail

resetLearningImpl

public void resetLearningImpl()

Description copied from class: AbstractClassifier

Resets this classifier. It must be similar to starting a new classifier from scratch.

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:

resetLearningImpl in class OzaBag

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

isRandomizable

public boolean isRandomizable()

Description copied from interface: Classifier

Gets whether this classifier needs a random seed. Examples of methods that needs a random seed are bagging and boosting.

Specified by:

isRandomizable in interface Classifier

Overrides:

isRandomizable in class OzaBag

Returns:

true if the classifier needs a random seed.

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 OzaBag

Parameters:

x - the instance to be classified

Returns:

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