MOA 12.03
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moa.classifiers.meta.OzaBoostAdwin Class Reference

Boosting for evolving data streams using ADWIN. More...

Inheritance diagram for moa.classifiers.meta.OzaBoostAdwin:
Collaboration diagram for moa.classifiers.meta.OzaBoostAdwin:

List of all members.

Public Member Functions

String getPurposeString ()
 Gets the purpose of this object.
void resetLearningImpl ()
 Resets this classifier.
void trainOnInstanceImpl (Instance inst)
 Trains this classifier incrementally using the given instance.
double[] getVotesForInstance (Instance inst)
 Predicts the class memberships for a given instance.
double[] getVotesForInstanceBinary (Instance inst)
boolean isRandomizable ()
 Gets whether this classifier needs a random seed.
void getModelDescription (StringBuilder out, int indent)
 Returns a string representation of the model.
Classifier[] getSubClassifiers ()
 Gets the classifiers of this ensemble.

Public Attributes

ClassOption baseLearnerOption
IntOption ensembleSizeOption
FlagOption pureBoostOption
FloatOption deltaAdwinOption
FlagOption outputCodesOption
FlagOption sammeOption

Protected Member Functions

double getEnsembleMemberWeight (int i)
Measurement[] getModelMeasurementsImpl ()
 Gets the current measurements of this classifier.

Protected Attributes

Classifier[] ensemble
double[] scms
double[] swms
ADWIN[] ADError
int numberOfChangesDetected
int[][] matrixCodes
boolean initMatrixCodes = false
double logKm1 = 0.0
int Km1 = 1
boolean initKm1 = false

Detailed Description

Boosting for evolving data streams using ADWIN.

Author:
Albert Bifet (abifet at cs dot waikato dot ac dot nz)
Version:
Revision:
7

Definition at line 40 of file OzaBoostAdwin.java.


Member Function Documentation

double moa.classifiers.meta.OzaBoostAdwin.getEnsembleMemberWeight ( int  i) [protected]

Definition at line 200 of file OzaBoostAdwin.java.

Referenced by moa.classifiers.meta.OzaBoostAdwin.getVotesForInstance(), and moa.classifiers.meta.OzaBoostAdwin.getVotesForInstanceBinary().

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void moa.classifiers.meta.OzaBoostAdwin.getModelDescription ( StringBuilder  out,
int  indent 
) [virtual]

Returns a string representation of the model.

Parameters:
outthe stringbuilder to add the description
indentthe number of characters to indent

Implements moa.classifiers.AbstractClassifier.

Definition at line 262 of file OzaBoostAdwin.java.

Measurement [] moa.classifiers.meta.OzaBoostAdwin.getModelMeasurementsImpl ( ) [protected, virtual]

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.

Returns:
an array of measurements to be used in evaluation tasks

Implements moa.classifiers.AbstractClassifier.

Definition at line 267 of file OzaBoostAdwin.java.

String moa.classifiers.meta.OzaBoostAdwin.getPurposeString ( )

Gets the purpose of this object.

Returns:
the string with the purpose of this object

Reimplemented from moa.classifiers.AbstractClassifier.

Definition at line 45 of file OzaBoostAdwin.java.

Classifier [] moa.classifiers.meta.OzaBoostAdwin.getSubClassifiers ( )

Gets the classifiers of this ensemble.

Returns null if this classifier is a single classifier.

Returns:
an array of the classifiers of the ensemble

Reimplemented from moa.classifiers.AbstractClassifier.

Definition at line 275 of file OzaBoostAdwin.java.

double [] moa.classifiers.meta.OzaBoostAdwin.getVotesForInstance ( Instance  inst)

Predicts the class memberships for a given instance.

If an instance is unclassified, the returned array elements must be all zero.

Parameters:
instthe instance to be classified
Returns:
an array containing the estimated membership probabilities of the test instance in each class

Implements moa.classifiers.Classifier.

Definition at line 209 of file OzaBoostAdwin.java.

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double [] moa.classifiers.meta.OzaBoostAdwin.getVotesForInstanceBinary ( Instance  inst)

Definition at line 230 of file OzaBoostAdwin.java.

Referenced by moa.classifiers.meta.OzaBoostAdwin.getVotesForInstance().

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boolean moa.classifiers.meta.OzaBoostAdwin.isRandomizable ( )

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.

Implements moa.classifiers.Classifier.

Definition at line 257 of file OzaBoostAdwin.java.

void moa.classifiers.meta.OzaBoostAdwin.resetLearningImpl ( ) [virtual]

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.

Implements moa.classifiers.AbstractClassifier.

Definition at line 88 of file OzaBoostAdwin.java.

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void moa.classifiers.meta.OzaBoostAdwin.trainOnInstanceImpl ( Instance  inst) [virtual]

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.

Parameters:
instthe instance to be used for training

Implements moa.classifiers.AbstractClassifier.

Definition at line 112 of file OzaBoostAdwin.java.

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Member Data Documentation

Initial value:
 new ClassOption("baseLearner", 'l',
            "Classifier to train.", Classifier.class, "trees.HoeffdingTree")

Definition at line 49 of file OzaBoostAdwin.java.

Referenced by moa.classifiers.meta.OzaBoostAdwin.resetLearningImpl().

Initial value:
 new FloatOption("deltaAdwin", 'a',
            "Delta of Adwin change detection", 0.002, 0.0, 1.0)

Definition at line 58 of file OzaBoostAdwin.java.

Referenced by moa.classifiers.meta.OzaBoostAdwin.resetLearningImpl(), and moa.classifiers.meta.OzaBoostAdwin.trainOnInstanceImpl().

Initial value:
 new IntOption("ensembleSize", 's',
            "The number of models to boost.", 10, 1, Integer.MAX_VALUE)

Definition at line 52 of file OzaBoostAdwin.java.

Referenced by moa.classifiers.meta.OzaBoostAdwin.resetLearningImpl().

Initial value:
 new FlagOption("pureBoost", 'p',
            "Boost with weights only; no poisson.")

Definition at line 55 of file OzaBoostAdwin.java.

Referenced by moa.classifiers.meta.OzaBoostAdwin.trainOnInstanceImpl().


The documentation for this class was generated from the following file:
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