Uses of Interface
moa.classifiers.Classifier

Packages that use Classifier

Package	Description
moa.classifiers
moa.classifiers.active
moa.classifiers.bayes
moa.classifiers.drift
moa.classifiers.functions
moa.classifiers.lazy
moa.classifiers.meta
moa.classifiers.multilabel
moa.classifiers.multilabel.meta
moa.classifiers.rules
moa.classifiers.rules.functions
moa.classifiers.trees
moa.evaluation
moa.learners
moa.tasks
weka.classifiers.meta

Uses of Classifier in moa.classifiers

Classes in moa.classifiers that implement Classifier

Modifier and Type	Class and Description
class	AbstractClassifier Abstract Classifier.

Methods in moa.classifiers that return Classifier

Modifier and Type	Method and Description
Classifier	Classifier.copy() Produces a copy of this classifier.
Classifier	AbstractClassifier.copy()
Classifier[]	Classifier.getSubClassifiers() Gets the classifiers of this ensemble.
Classifier[]	AbstractClassifier.getSubClassifiers()

Uses of Classifier in moa.classifiers.active

Classes in moa.classifiers.active that implement Classifier

Modifier and Type	Class and Description
class	ActiveClassifier Active learning setting for evolving data streams.

Fields in moa.classifiers.active declared as Classifier

Modifier and Type	Field and Description
Classifier	ActiveClassifier.classifier

Uses of Classifier in moa.classifiers.bayes

Classes in moa.classifiers.bayes that implement Classifier

Modifier and Type	Class and Description
class	NaiveBayes Naive Bayes incremental learner.
class	NaiveBayesMultinomial Class for building and using a multinomial Naive Bayes classifier.

Uses of Classifier in moa.classifiers.drift

Classes in moa.classifiers.drift that implement Classifier

Modifier and Type	Class and Description
class	DriftDetectionMethodClassifier Class for handling concept drift datasets with a wrapper on a classifier.
class	SingleClassifierDrift Class for handling concept drift datasets with a wrapper on a classifier.

Fields in moa.classifiers.drift declared as Classifier

Modifier and Type	Field and Description
protected Classifier	DriftDetectionMethodClassifier.classifier
protected Classifier	DriftDetectionMethodClassifier.newclassifier

Uses of Classifier in moa.classifiers.functions

Classes in moa.classifiers.functions that implement Classifier

Modifier and Type	Class and Description
class	MajorityClass Majority class learner.
class	NoChange NoChange class classifier.
class	SGD Implements stochastic gradient descent for learning various linear models (binary class SVM, binary class logistic regression and linear regression).
class	SGDMultiClass Implements stochastic gradient descent for learning various linear models (binary class SVM, binary class logistic regression and linear regression).
class	SPegasos Implements the stochastic variant of the Pegasos (Primal Estimated sub-GrAdient SOlver for SVM) method of Shalev-Shwartz et al.

Uses of Classifier in moa.classifiers.lazy

Classes in moa.classifiers.lazy that implement Classifier

Modifier and Type	Class and Description
class	kNN k Nearest Neighbor.
class	kNNwithPAW k Nearest Neighbor ADAPTIVE with PAW.
class	kNNwithPAWandADWIN k Nearest Neighbor ADAPTIVE with ADWIN+PAW.

Uses of Classifier in moa.classifiers.meta

Classes in moa.classifiers.meta that implement Classifier

Modifier and Type	Class and Description
class	AccuracyUpdatedEnsemble The revised version of the Accuracy Updated Ensemble as proposed by Brzezinski and Stefanowski in "Reacting to Different Types of Concept Drift: The Accuracy Updated Ensemble Algorithm", IEEE Trans.
class	AccuracyWeightedEnsemble The Accuracy Weighted Ensemble classifier as proposed by Wang et al.
class	ADACC Anticipative and Dynamic Adaptation to Concept Changes.
class	DACC Dynamic Adaptation to Concept Changes.
class	LeveragingBag Leveraging Bagging for evolving data streams using ADWIN.
class	LimAttClassifier Ensemble Combining Restricted Hoeffding Trees using Stacking.
class	OCBoost Online Coordinate boosting for two classes evolving data streams.
class	OnlineAccuracyUpdatedEnsemble The online version of the Accuracy Updated Ensemble as proposed by Brzezinski and Stefanowski in "Combining block-based and online methods in learning ensembles from concept drifting data streams", Information Sciences, 2014.
class	OnlineSmoothBoost Incremental on-line boosting with Theoretical Justifications of Shang-Tse Chen, Hsuan-Tien Lin and Chi-Jen Lu.
class	OzaBag Incremental on-line bagging of Oza and Russell.
class	OzaBagAdwin Bagging for evolving data streams using ADWIN.
class	OzaBagASHT Bagging using trees of different size.
class	OzaBoost Incremental on-line boosting of Oza and Russell.
class	OzaBoostAdwin Boosting for evolving data streams using ADWIN.
class	RandomRules
class	TemporallyAugmentedClassifier Include labels of previous instances into the training data
class	WeightedMajorityAlgorithm Weighted majority algorithm for data streams.
class	WEKAClassifier Class for using a classifier from WEKA.

Fields in moa.classifiers.meta declared as Classifier

Modifier and Type	Field and Description
protected Classifier	TemporallyAugmentedClassifier.baseLearner
protected Classifier	AccuracyUpdatedEnsemble.candidate Candidate classifier.
protected Classifier	AccuracyWeightedEnsemble.candidateClassifier
protected Classifier[]	OzaBagAdwin.ensemble
protected Classifier[]	LimAttClassifier.ensemble
protected Classifier[]	DACC.ensemble Ensemble of classifiers
protected Classifier[]	LeveragingBag.ensemble
protected Classifier[]	RandomRules.ensemble
protected Classifier[]	OnlineSmoothBoost.ensemble
protected Classifier[]	OCBoost.ensemble
protected Classifier[]	OzaBoost.ensemble
protected Classifier[]	OzaBoostAdwin.ensemble
protected Classifier[]	AccuracyWeightedEnsemble.ensemble
protected Classifier[]	WeightedMajorityAlgorithm.ensemble
protected Classifier[]	OzaBag.ensemble
protected Classifier[]	AccuracyUpdatedEnsemble.learners Ensemble classifiers.
protected Classifier[]	AccuracyWeightedEnsemble.storedLearners

Methods in moa.classifiers.meta that return Classifier

Modifier and Type	Method and Description
protected Classifier	AccuracyWeightedEnsemble.addToStored(Classifier newClassifier, double newClassifiersWeight) Adds a classifier to the storage.
protected Classifier	AccuracyUpdatedEnsemble.addToStored(Classifier newClassifier, double newClassifiersWeight) Adds a classifier to the storage.
Classifier[]	OzaBagAdwin.getSubClassifiers()
Classifier[]	LimAttClassifier.getSubClassifiers()
Classifier[]	DACC.getSubClassifiers()
Classifier[]	LeveragingBag.getSubClassifiers()
Classifier[]	RandomRules.getSubClassifiers()
Classifier[]	OnlineSmoothBoost.getSubClassifiers()
Classifier[]	OCBoost.getSubClassifiers()
Classifier[]	OzaBoost.getSubClassifiers()
Classifier[]	OzaBoostAdwin.getSubClassifiers()
Classifier[]	AccuracyWeightedEnsemble.getSubClassifiers()
Classifier[]	WeightedMajorityAlgorithm.getSubClassifiers()
Classifier[]	AccuracyUpdatedEnsemble.getSubClassifiers()
Classifier[]	OzaBag.getSubClassifiers()
Classifier[]	OnlineAccuracyUpdatedEnsemble.getSubClassifiers()

Methods in moa.classifiers.meta with parameters of type Classifier

Modifier and Type	Method and Description
protected Classifier	AccuracyWeightedEnsemble.addToStored(Classifier newClassifier, double newClassifiersWeight) Adds a classifier to the storage.
protected Classifier	AccuracyUpdatedEnsemble.addToStored(Classifier newClassifier, double newClassifiersWeight) Adds a classifier to the storage.
protected double	AccuracyWeightedEnsemble.computeCandidateWeight(Classifier candidate, weka.core.Instances chunk, int numFolds) Computes the weight of a candidate classifier.
protected double	AccuracyUpdatedEnsemble.computeMse(Classifier learner, weka.core.Instances chunk) Computes the MSE of a learner for a given chunk of examples.
protected double	AccuracyWeightedEnsemble.computeWeight(Classifier learner, weka.core.Instances chunk) Computes the weight of a given classifie.

Constructors in moa.classifiers.meta with parameters of type Classifier

Constructor and Description
OnlineAccuracyUpdatedEnsemble.ClassifierWithMemory(Classifier classifier, int windowSize)

Uses of Classifier in moa.classifiers.multilabel

Classes in moa.classifiers.multilabel that implement Classifier

Modifier and Type	Class and Description
class	HoeffdingTreeClassifLeaves Hoeffding Tree that have a classifier at the leaves.
class	MajorityLabelset Majority Labelset classifier.
class	MEKAClassifier Class for using a MEKA classifier.
class	MultilabelHoeffdingTree Hoeffding Tree for classifying multi-label data.

Fields in moa.classifiers.multilabel declared as Classifier

Modifier and Type	Field and Description
protected Classifier	HoeffdingTreeClassifLeaves.LearningNodeClassifier.classifier

Methods in moa.classifiers.multilabel that return Classifier

Modifier and Type	Method and Description
Classifier	MultilabelHoeffdingTree.MultilabelLearningNodeClassifier.getClassifier()
Classifier	HoeffdingTreeClassifLeaves.LearningNodeClassifier.getClassifier()

Methods in moa.classifiers.multilabel with parameters of type Classifier

Modifier and Type	Method and Description
protected HoeffdingTree.LearningNode	MultilabelHoeffdingTree.newLearningNode(double[] initialClassObservations, Classifier cl)
protected HoeffdingTree.LearningNode	HoeffdingTreeClassifLeaves.newLearningNode(double[] initialClassObservations, Classifier cl)

Constructors in moa.classifiers.multilabel with parameters of type Classifier

Constructor and Description
HoeffdingTreeClassifLeaves.LearningNodeClassifier(double[] initialClassObservations, Classifier cl, HoeffdingTreeClassifLeaves ht)
MultilabelHoeffdingTree.MultilabelLearningNodeClassifier(double[] initialClassObservations, Classifier cl, MultilabelHoeffdingTree ht)

Uses of Classifier in moa.classifiers.multilabel.meta

Classes in moa.classifiers.multilabel.meta that implement Classifier

Modifier and Type	Class and Description
class	MLOzaBag OzaBag for Multi-label data.
class	MLOzaBagAdwin MLOzaBagAdwin: Changes the way to compute accuracy as an input for Adwin

Uses of Classifier in moa.classifiers.rules

Classes in moa.classifiers.rules that implement Classifier

Modifier and Type	Class and Description
class	AbstractAMRules
class	AMRulesRegressor
class	RuleClassifier This classifier learn ordered and unordered rule set from data stream.
class	RuleClassifierNBayes This classifier learn ordered and unordered rule set from data stream with naive Bayes learners.

Uses of Classifier in moa.classifiers.rules.functions

Classes in moa.classifiers.rules.functions that implement Classifier

Modifier and Type	Class and Description
class	FadingTargetMean
class	Perceptron
class	TargetMean

Uses of Classifier in moa.classifiers.trees

Classes in moa.classifiers.trees that implement Classifier

Modifier and Type	Class and Description
class	AdaHoeffdingOptionTree Adaptive decision option tree for streaming data with adaptive Naive Bayes classification at leaves.
class	ASHoeffdingTree Adaptive Size Hoeffding Tree used in Bagging using trees of different size.
class	DecisionStump Decision trees of one level. Parameters:
class	FIMTDD
class	HoeffdingAdaptiveTree Hoeffding Adaptive Tree for evolving data streams.
class	HoeffdingOptionTree Hoeffding Option Tree.
class	HoeffdingTree Hoeffding Tree or VFDT.
class	LimAttHoeffdingTree Hoeffding decision trees with a restricted number of attributes for data streams.
class	ORTO
class	RandomHoeffdingTree Random decision trees for data streams.

Uses of Classifier in moa.evaluation

Constructors in moa.evaluation with parameters of type Classifier

Constructor and Description
LearningEvaluation(ClassificationPerformanceEvaluator cpe, Classifier model)
LearningEvaluation(Measurement[] evaluationMeasurements, ClassificationPerformanceEvaluator cpe, Classifier model)

Uses of Classifier in moa.learners

Classes in moa.learners that implement Classifier

Modifier and Type	Class and Description
class	ChangeDetectorLearner Class for detecting concept drift and to be used as a learner.

Uses of Classifier in moa.tasks

Constructors in moa.tasks with parameters of type Classifier

Constructor and Description
EvaluateModel(Classifier model, InstanceStream stream, ClassificationPerformanceEvaluator evaluator, int maxInstances)
EvaluateModelRegression(Classifier model, InstanceStream stream, ClassificationPerformanceEvaluator evaluator, int maxInstances)
LearnModel(Classifier learner, InstanceStream stream, int maxInstances, int numPasses)
LearnModelRegression(Classifier learner, InstanceStream stream, int maxInstances, int numPasses)

Uses of Classifier in weka.classifiers.meta

Fields in weka.classifiers.meta declared as Classifier

Modifier and Type	Field and Description
protected Classifier	MOA.m_ActualClassifier the actual moa classifier to use for learning.