moa.classifiers.trees

Class ORTO

java.lang.Object

moa.AbstractMOAObject

moa.options.AbstractOptionHandler

moa.classifiers.AbstractClassifier

moa.classifiers.trees.ORTO

All Implemented Interfaces:

Serializable, Classifier, Regressor, AWTRenderable, MOAObject, OptionHandler

public class ORTO
extends AbstractClassifier
implements Regressor

See Also:

Serialized Form

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	ORTO.ActiveLearningNode
static class	ORTO.InnerNode
static class	ORTO.Node
static class	ORTO.OptionNode
static class	ORTO.ORTOPerceptron A Perceptron classifier modified to conform to the specifications of Ikonomovska et al.
static class	ORTO.SplitNode

Field Summary

Fields

Modifier and Type	Field and Description
protected double	activeLeafByteSizeEstimate
protected boolean	Adaptable
FloatOption	AlternateTreeFadingFactorOption
IntOption	AlternateTreeTimeOption
IntOption	AlternateTreeTMinOption
protected double	byteSizeEstimateOverheadFraction
IntOption	gracePeriodOption
protected double	inactiveLeafByteSizeEstimate
protected double	initLearnRate
FlagOption	LearningRatioDecayOrConstOption
FloatOption	LearningRatioOption
protected double	learnRateDecay
protected int	maxDepth
int	maxID
IntOption	MaxOptionLevelOption
IntOption	MaxTreesOption
protected ArrayList<ORTO.InnerNode>	nodesToAdapt
ClassOption	numericEstimatorOption
FloatOption	OptionDecayFactorOption
FloatOption	OptionFadingFactorOption
MultiChoiceOption	OptionNodeAggregationOption
FloatOption	PageHinckleyAlphaOption
IntOption	PageHinckleyThresholdOption
FlagOption	removePoorAttsOption
FloatOption	splitConfidenceOption
ClassOption	splitCriterionOption
FloatOption	tieThresholdOption
protected ORTO.Node	treeRoot

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
ORTO()

Method Summary

Methods

Modifier and Type	Method and Description
int	calcByteSize()
protected void	checkRoot()
static double	computeHoeffdingBound(double range, double confidence, double n)
protected ORTO.Node	findWorstOption()
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.
protected AttributeClassObserver	newNumericClassObserver()
protected void	removeExcessTrees()
void	resetLearningImpl() Resets this classifier.
void	trainOnInstanceImpl(weka.core.Instance inst) Method for updating (training) the model using a new instance

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

treeRoot

protected ORTO.Node treeRoot

maxDepth

protected int maxDepth

inactiveLeafByteSizeEstimate

protected double inactiveLeafByteSizeEstimate

activeLeafByteSizeEstimate

protected double activeLeafByteSizeEstimate

byteSizeEstimateOverheadFraction

protected double byteSizeEstimateOverheadFraction

nodesToAdapt

protected ArrayList<ORTO.InnerNode> nodesToAdapt

Adaptable

protected boolean Adaptable

initLearnRate

protected double initLearnRate

learnRateDecay

protected double learnRateDecay

maxID

public int maxID

PageHinckleyAlphaOption

public FloatOption PageHinckleyAlphaOption

PageHinckleyThresholdOption

public IntOption PageHinckleyThresholdOption

AlternateTreeFadingFactorOption

public FloatOption AlternateTreeFadingFactorOption

AlternateTreeTMinOption

public IntOption AlternateTreeTMinOption

AlternateTreeTimeOption

public IntOption AlternateTreeTimeOption

LearningRatioOption

public FloatOption LearningRatioOption

LearningRatioDecayOrConstOption

public FlagOption LearningRatioDecayOrConstOption

MaxTreesOption

public IntOption MaxTreesOption

MaxOptionLevelOption

public IntOption MaxOptionLevelOption

OptionDecayFactorOption

public FloatOption OptionDecayFactorOption

splitCriterionOption

public ClassOption splitCriterionOption

numericEstimatorOption

public ClassOption numericEstimatorOption

gracePeriodOption

public IntOption gracePeriodOption

splitConfidenceOption

public FloatOption splitConfidenceOption

tieThresholdOption

public FloatOption tieThresholdOption

removePoorAttsOption

public FlagOption removePoorAttsOption

OptionNodeAggregationOption

public MultiChoiceOption OptionNodeAggregationOption

OptionFadingFactorOption

public FloatOption OptionFadingFactorOption

Constructor Detail

ORTO

public ORTO()

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

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

Returns:

true if the classifier needs a random seed.

checkRoot

protected void checkRoot()

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

calcByteSize

public int calcByteSize()

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

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.

Specified by:

getVotesForInstance in interface Classifier

Parameters:

inst - the instance to be classified

Returns:

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

trainOnInstanceImpl

public void trainOnInstanceImpl(weka.core.Instance inst)

Method for updating (training) the model using a new instance

Specified by:

trainOnInstanceImpl in class AbstractClassifier

Parameters:

inst - the instance to be used for training

newNumericClassObserver

protected AttributeClassObserver newNumericClassObserver()

computeHoeffdingBound

public static double computeHoeffdingBound(double range,
                           double confidence,
                           double n)

findWorstOption

protected ORTO.Node findWorstOption()

removeExcessTrees

protected void removeExcessTrees()