Uses of Interface
moa.gui.AWTRenderable

Packages that use AWTRenderable

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.clusterers
moa.clusterers.clustream
moa.clusterers.clustree
moa.clusterers.denstream
moa.clusterers.outliers
moa.clusterers.outliers.AbstractC
moa.clusterers.outliers.Angiulli
moa.clusterers.outliers.AnyOut
moa.clusterers.outliers.MCOD
moa.clusterers.outliers.SimpleCOD
moa.clusterers.streamkm
moa.learners

Uses of AWTRenderable in moa.classifiers

Subinterfaces of AWTRenderable in moa.classifiers

Modifier and Type	Interface and Description
interface	Classifier Classifier interface for incremental classification models.

Classes in moa.classifiers that implement AWTRenderable

Modifier and Type	Class and Description
class	AbstractClassifier Abstract Classifier.

Uses of AWTRenderable in moa.classifiers.active

Classes in moa.classifiers.active that implement AWTRenderable

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

Uses of AWTRenderable in moa.classifiers.bayes

Classes in moa.classifiers.bayes that implement AWTRenderable

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 AWTRenderable in moa.classifiers.drift

Classes in moa.classifiers.drift that implement AWTRenderable

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.

Uses of AWTRenderable in moa.classifiers.functions

Classes in moa.classifiers.functions that implement AWTRenderable

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 AWTRenderable in moa.classifiers.lazy

Classes in moa.classifiers.lazy that implement AWTRenderable

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 AWTRenderable in moa.classifiers.meta

Classes in moa.classifiers.meta that implement AWTRenderable

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.

Uses of AWTRenderable in moa.classifiers.multilabel

Classes in moa.classifiers.multilabel that implement AWTRenderable

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.

Uses of AWTRenderable in moa.classifiers.multilabel.meta

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

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 AWTRenderable in moa.classifiers.rules

Classes in moa.classifiers.rules that implement AWTRenderable

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 AWTRenderable in moa.classifiers.rules.functions

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

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

Uses of AWTRenderable in moa.classifiers.trees

Classes in moa.classifiers.trees that implement AWTRenderable

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 AWTRenderable in moa.clusterers

Subinterfaces of AWTRenderable in moa.clusterers

Modifier and Type	Interface and Description
interface	Clusterer

Classes in moa.clusterers that implement AWTRenderable

Modifier and Type	Class and Description
class	AbstractClusterer
class	ClusterGenerator
class	CobWeb Class implementing the Cobweb and Classit clustering algorithms.
class	WekaClusteringAlgorithm

Uses of AWTRenderable in moa.clusterers.clustream

Classes in moa.clusterers.clustream that implement AWTRenderable

Modifier and Type	Class and Description
class	Clustream Citation: CluStream: Charu C.
class	WithKmeans

Uses of AWTRenderable in moa.clusterers.clustree

Classes in moa.clusterers.clustree that implement AWTRenderable

Modifier and Type	Class and Description
class	ClusTree Citation: ClusTree: Philipp Kranen, Ira Assent, Corinna Baldauf, Thomas Seidl: The ClusTree: indexing micro-clusters for anytime stream mining.

Uses of AWTRenderable in moa.clusterers.denstream

Classes in moa.clusterers.denstream that implement AWTRenderable

Modifier and Type	Class and Description
class	WithDBSCAN

Uses of AWTRenderable in moa.clusterers.outliers

Classes in moa.clusterers.outliers that implement AWTRenderable

Modifier and Type	Class and Description
class	MyBaseOutlierDetector

Uses of AWTRenderable in moa.clusterers.outliers.AbstractC

Classes in moa.clusterers.outliers.AbstractC that implement AWTRenderable

Modifier and Type	Class and Description
class	AbstractC
class	AbstractCBase

Uses of AWTRenderable in moa.clusterers.outliers.Angiulli

Classes in moa.clusterers.outliers.Angiulli that implement AWTRenderable

Modifier and Type	Class and Description
class	ApproxSTORM
class	ExactSTORM
class	STORMBase

Uses of AWTRenderable in moa.clusterers.outliers.AnyOut

Classes in moa.clusterers.outliers.AnyOut that implement AWTRenderable

Modifier and Type	Class and Description
class	AnyOut
class	AnyOutCore

Uses of AWTRenderable in moa.clusterers.outliers.MCOD

Classes in moa.clusterers.outliers.MCOD that implement AWTRenderable

Modifier and Type	Class and Description
class	MCOD
class	MCODBase

Uses of AWTRenderable in moa.clusterers.outliers.SimpleCOD

Classes in moa.clusterers.outliers.SimpleCOD that implement AWTRenderable

Modifier and Type	Class and Description
class	SimpleCOD
class	SimpleCODBase

Uses of AWTRenderable in moa.clusterers.streamkm

Classes in moa.clusterers.streamkm that implement AWTRenderable

Modifier and Type	Class and Description
class	StreamKM

Uses of AWTRenderable in moa.learners

Classes in moa.learners that implement AWTRenderable

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