moa.classifiers.drift

Class DriftDetectionMethodClassifier

java.lang.Object

moa.AbstractMOAObject

moa.options.AbstractOptionHandler

moa.classifiers.AbstractClassifier

moa.classifiers.drift.DriftDetectionMethodClassifier

All Implemented Interfaces:

Serializable, Classifier, AWTRenderable, MOAObject, OptionHandler

Direct Known Subclasses:

SingleClassifierDrift

public class DriftDetectionMethodClassifier
extends AbstractClassifier

Class for handling concept drift datasets with a wrapper on a classifier.

Valid options are:

-l classname
Specify the full class name of a classifier as the basis for the concept drift classifier.

-d Drift detection method to use

Version:

1.1

Author:

Manuel Baena (mbaena@lcc.uma.es)

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
ClassOption	baseLearnerOption
protected int	changeDetected
protected Classifier	classifier
static int	DDM_INCONTROL_LEVEL
static int	DDM_OUTCONTROL_LEVEL
static int	DDM_WARNING_LEVEL
protected int	ddmLevel
protected ChangeDetector	driftDetectionMethod
ClassOption	driftDetectionMethodOption
protected Classifier	newclassifier
protected boolean	newClassifierReset
protected int	warningDetected

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
DriftDetectionMethodClassifier()

Method Summary

Methods

Modifier and Type	Method and Description
void	getModelDescription(StringBuilder out, int indent) Returns a string representation of the model.
protected Measurement[]	getModelMeasurementsImpl() Gets the current measurements of this classifier. The reason for ...Impl methods: ease programmer burden by not requiring them to remember calls to super in overridden methods.
String	getPurposeString() Gets the purpose of this object
double[]	getVotesForInstance(weka.core.Instance inst) Predicts the class memberships for a given instance.
boolean	isRandomizable() Gets whether this classifier needs a random seed.
void	resetLearningImpl() Resets this classifier.
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.AbstractClassifier

contextIsCompatible, copy, correctlyClassifies, getAttributeNameString, getAWTRenderer, getClassLabelString, getClassNameString, getDescription, getModelContext, getModelMeasurements, getNominalValueString, getSubClassifiers, modelAttIndexToInstanceAttIndex, modelAttIndexToInstanceAttIndex, prepareForUseImpl, resetLearning, setModelContext, 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

baseLearnerOption

public ClassOption baseLearnerOption

driftDetectionMethodOption

public ClassOption driftDetectionMethodOption

classifier

protected Classifier classifier

newclassifier

protected Classifier newclassifier

driftDetectionMethod

protected ChangeDetector driftDetectionMethod

newClassifierReset

protected boolean newClassifierReset

ddmLevel

protected int ddmLevel

DDM_INCONTROL_LEVEL

public static final int DDM_INCONTROL_LEVEL

See Also:

Constant Field Values

DDM_WARNING_LEVEL

public static final int DDM_WARNING_LEVEL

See Also:

Constant Field Values

DDM_OUTCONTROL_LEVEL

public static final int DDM_OUTCONTROL_LEVEL

See Also:

Constant Field Values

changeDetected

protected int changeDetected

warningDetected

protected int warningDetected

Constructor Detail

DriftDetectionMethodClassifier

public DriftDetectionMethodClassifier()

Method Detail

getPurposeString

public String getPurposeString()

Description copied from interface: OptionHandler

Gets the purpose of this object

Specified by:

getPurposeString in interface OptionHandler

Overrides:

getPurposeString in class AbstractClassifier

Returns:

the string with the purpose of this object

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.

Specified by:

resetLearningImpl in class AbstractClassifier

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.

Specified by:

trainOnInstanceImpl in class AbstractClassifier

Parameters:

inst - the instance to be used for training

getVotesForInstance

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

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.

Parameters:

inst - the instance to be classified

Returns:

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

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.

Returns:

true if the classifier needs a random seed.

getModelDescription

public void getModelDescription(StringBuilder out,
                       int indent)

Description copied from class: AbstractClassifier

Returns a string representation of the model.

Specified by:

getModelDescription in class AbstractClassifier

Parameters:

out - the stringbuilder to add the description

indent - the number of characters to indent

getModelMeasurementsImpl

protected Measurement[] getModelMeasurementsImpl()

Description copied from class: AbstractClassifier

Gets the current measurements of this classifier.

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.

Specified by:

getModelMeasurementsImpl in class AbstractClassifier

Returns:

an array of measurements to be used in evaluation tasks