Modifier and Type | Interface and Description |
---|---|
interface |
Classifier
Classifier interface for incremental classification models.
|
Modifier and Type | Class and Description |
---|---|
class |
AbstractClassifier
Abstract Classifier.
|
Modifier and Type | Class and Description |
---|---|
class |
ActiveClassifier
Active learning setting for evolving data streams.
|
Modifier and Type | Class and Description |
---|---|
class |
NaiveBayes
Naive Bayes incremental learner.
|
class |
NaiveBayesMultinomial
Class for building and using a multinomial Naive
Bayes classifier.
|
Modifier and Type | Interface and Description |
---|---|
interface |
AttributeClassObserver
Interface for observing the class data distribution for an attribute.
|
interface |
DiscreteAttributeClassObserver
Interface for observing the class data distribution for a discrete (nominal) attribute.
|
interface |
NumericAttributeClassObserver
Interface for observing the class data distribution for a numeric attribute.
|
Modifier and Type | Class and Description |
---|---|
class |
BinaryTreeNumericAttributeClassObserver
Class for observing the class data distribution for a numeric attribute using a binary tree.
|
class |
BinaryTreeNumericAttributeClassObserverRegression
Class for observing the class data distribution for a numeric attribute using a binary tree.
|
class |
FIMTDDNumericAttributeClassObserver |
class |
GaussianNumericAttributeClassObserver
Class for observing the class data distribution for a numeric attribute using gaussian estimators.
|
class |
GreenwaldKhannaNumericAttributeClassObserver
Class for observing the class data distribution for a numeric attribute using Greenwald and Khanna methodology.
|
class |
NominalAttributeClassObserver
Class for observing the class data distribution for a nominal attribute.
|
class |
NullAttributeClassObserver
Class for observing the class data distribution for a null attribute.
|
class |
VFMLNumericAttributeClassObserver
Class for observing the class data distribution for a numeric attribute as in VFML.
|
Modifier and Type | Interface and Description |
---|---|
interface |
ChangeDetector
Change Detector interface to implement methods that detects change.
|
Modifier and Type | Class and Description |
---|---|
class |
AbstractChangeDetector
Abstract Change Detector.
|
class |
ADWINChangeDetector
Drift detection method based in ADWIN.
|
class |
CusumDM
Drift detection method based in Cusum
|
class |
DDM
Drift detection method based in DDM method of Joao Gama SBIA 2004.
|
class |
EDDM
Drift detection method based in EDDM method of Manuel Baena et al.
|
class |
EnsembleDriftDetectionMethods
Ensemble Drift detection method
|
class |
EWMAChartDM
Drift detection method based in EWMA Charts of Ross, Adams, Tasoulis and Hand
2012
|
class |
GeometricMovingAverageDM
Drift detection method based in Geometric Moving Average Test
|
class |
HDDM_A_Test
Online drift detection method based on Hoeffding's bounds.
|
class |
HDDM_W_Test
Online drift detection method based on McDiarmid's bounds.
|
class |
PageHinkleyDM
Drift detection method based in Page Hinkley Test.
|
class |
SeqDrift1ChangeDetector
SeqDrift1ChangeDetector.java.
|
class |
SeqDrift2ChangeDetector
SeqDriftChangeDetector.java.
|
Modifier and Type | Interface and Description |
---|---|
interface |
SplitCriterion
Interface for computing splitting criteria.
|
Modifier and Type | Class and Description |
---|---|
class |
GiniSplitCriterion
Class for computing splitting criteria using Gini
with respect to distributions of class values.
|
class |
InfoGainSplitCriterion
Class for computing splitting criteria using information gain
with respect to distributions of class values.
|
class |
InfoGainSplitCriterionMultilabel
Class for computing splitting criteria using information gain with respect to
distributions of class values for Multilabel data.
|
class |
SDRSplitCriterion |
class |
VarianceReductionSplitCriterion |
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.
|
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.
|
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.
|
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.
|
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.
|
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
|
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.
|
Modifier and Type | Class and Description |
---|---|
class |
FIMTDDNumericAttributeClassLimitObserver |
Modifier and Type | Class and Description |
---|---|
class |
SDRSplitCriterionAMRules |
Modifier and Type | Class and Description |
---|---|
class |
FadingTargetMean |
class |
Perceptron |
class |
TargetMean |
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.
|
Modifier and Type | Interface and Description |
---|---|
interface |
Clusterer |
Modifier and Type | Class and Description |
---|---|
class |
AbstractClusterer |
class |
ClusterGenerator |
class |
CobWeb
Class implementing the Cobweb and Classit clustering algorithms.
|
class |
WekaClusteringAlgorithm |
Modifier and Type | Class and Description |
---|---|
class |
Clustream
Citation: CluStream: Charu C.
|
class |
WithKmeans |
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.
|
Modifier and Type | Class and Description |
---|---|
class |
WithDBSCAN |
Modifier and Type | Class and Description |
---|---|
class |
MyBaseOutlierDetector |
Modifier and Type | Class and Description |
---|---|
class |
AbstractC |
class |
AbstractCBase |
Modifier and Type | Class and Description |
---|---|
class |
ApproxSTORM |
class |
ExactSTORM |
class |
STORMBase |
Modifier and Type | Class and Description |
---|---|
class |
AnyOut |
class |
AnyOutCore |
Modifier and Type | Class and Description |
---|---|
class |
MCOD |
class |
MCODBase |
Modifier and Type | Class and Description |
---|---|
class |
SimpleCOD |
class |
SimpleCODBase |
Modifier and Type | Class and Description |
---|---|
class |
StreamKM |
Modifier and Type | Class and Description |
---|---|
class |
EWMAClassificationPerformanceEvaluator
Classification evaluator that updates evaluation results using an Exponential Weighted Moving Average.
|
class |
FadingFactorClassificationPerformanceEvaluator
Classification evaluator that updates evaluation results using a fading factor.
|
class |
MultilabelWindowClassificationPerformanceEvaluator
Multilabel Window Classification Performance Evaluator.
|
class |
WindowClassificationPerformanceEvaluator
Classification evaluator that updates evaluation results using a sliding
window.
|
class |
WindowRegressionPerformanceEvaluator
Regression evaluator that updates evaluation results using a sliding window.
|
Modifier and Type | Method and Description |
---|---|
static boolean |
OptionsConfigurationPanel.showEditOptionsDialog(Component parent,
String title,
OptionHandler optionHandler) |
Modifier and Type | Class and Description |
---|---|
class |
ChangeDetectorLearner
Class for detecting concept drift and to be used as a learner.
|
Modifier and Type | Class and Description |
---|---|
class |
AbstractOptionHandler
Abstract Option Handler.
|
Modifier and Type | Method and Description |
---|---|
OptionHandler |
AbstractOptionHandler.copy() |
OptionHandler |
OptionHandler.copy()
This method produces a copy of this object.
|
Modifier and Type | Class and Description |
---|---|
class |
MemRecommenderData |
Modifier and Type | Class and Description |
---|---|
class |
FlixsterDataset |
class |
JesterDataset |
class |
MovielensDataset |
Modifier and Type | Class and Description |
---|---|
class |
BaselinePredictor
A naive algorithm which combines the global mean of all the existing
ratings, the mean rating of the user and the mean rating of the item
to make a prediction.
|
class |
BRISMFPredictor
Implementation of the algorithm described in Scalable
Collaborative Filtering Approaches for Large Recommender
Systems (Gábor Takács, István Pilászy, Bottyán Németh,
and Domonkos Tikk).
|
Modifier and Type | Class and Description |
---|---|
class |
ArffFileStream
Stream reader of ARFF files.
|
class |
ConceptDriftRealStream
Stream generator that adds concept drift to examples in a stream with
different classes and attributes.
|
class |
ConceptDriftStream
Stream generator that adds concept drift to examples in a stream.
|
class |
FilteredStream
Class for representing a stream that is filtered.
|
class |
MultiFilteredStream
Class for representing a stream that is filtered.
|
Modifier and Type | Class and Description |
---|---|
class |
ClusteringStream |
class |
FileStream |
class |
RandomRBFGeneratorEvents |
Modifier and Type | Class and Description |
---|---|
class |
AbstractStreamFilter
Abstract Stream Filter.
|
class |
AddNoiseFilter
Filter for adding random noise to examples in a stream.
|
class |
CacheFilter
Filter for representing a stream that is cached in memory.
|
class |
ReplacingMissingValuesFilter
Replaces the missing values with another value according to the selected
strategy.
|
Modifier and Type | Class and Description |
---|---|
class |
AgrawalGenerator
Stream generator for Agrawal dataset.
|
class |
HyperplaneGenerator
Stream generator for Hyperplane data stream.
|
class |
LEDGenerator
Stream generator for the problem of predicting the digit displayed on a 7-segment LED display.
|
class |
LEDGeneratorDrift
Stream generator for the problem of predicting the digit displayed on a 7-segment LED display with drift.
|
class |
RandomRBFGenerator
Stream generator for a random radial basis function stream.
|
class |
RandomRBFGeneratorDrift
Stream generator for a random radial basis function stream with drift.
|
class |
RandomTreeGenerator
Stream generator for a stream based on a randomly generated tree..
|
class |
SEAGenerator
Stream generator for SEA concepts functions.
|
class |
STAGGERGenerator
Stream generator for STAGGER Concept functions.
|
class |
WaveformGenerator
Stream generator for the problem of predicting one of three waveform types.
|
class |
WaveformGeneratorDrift
Stream generator for the problem of predicting one of three waveform types with drift.
|
Modifier and Type | Class and Description |
---|---|
class |
AbruptChangeGenerator |
class |
AbstractConceptDriftGenerator |
class |
GradualChangeGenerator |
class |
NoChangeGenerator |
Modifier and Type | Class and Description |
---|---|
class |
MetaMultilabelGenerator
Stream generator for multilabel data.
|
class |
MultilabelArffFileStream
Stream reader for ARFF files of multilabel data.
|
Modifier and Type | Class and Description |
---|---|
class |
AbstractTask
Abstract Task.
|
class |
CacheShuffledStream
Task for storing and shuffling examples in memory.
|
class |
ConceptDriftMainTask |
class |
EvaluateClustering
Task for evaluating a clusterer on a stream.
|
class |
EvaluateConceptDrift
Task for evaluating a classifier on a stream by testing then training with each example in sequence.
|
class |
EvaluateInterleavedChunks |
class |
EvaluateInterleavedTestThenTrain
Task for evaluating a classifier on a stream by testing then training with
each example in sequence.
|
class |
EvaluateModel
Task for evaluating a static model on a stream.
|
class |
EvaluateModelRegression
Task for evaluating a static model on a stream.
|
class |
EvaluateOnlineRecommender
Test for evaluating a recommender by training and periodically testing
on samples from a rating dataset.
|
class |
EvaluatePeriodicHeldOutTest
Task for evaluating a classifier on a stream by periodically testing on a heldout set.
|
class |
EvaluatePrequential
Task for evaluating a classifier on a stream by testing then training with each example in sequence.
|
class |
EvaluatePrequentialRegression
Task for evaluating a classifier on a stream by testing then training with each example in sequence.
|
class |
LearnModel
Task for learning a model without any evaluation.
|
class |
LearnModelRegression
Task for learning a model without any evaluation.
|
class |
MainTask
Abstract Main Task.
|
class |
MeasureStreamSpeed
Task for measuring the speed of the stream.
|
class |
Plot
A task allowing to create and plot gnuplot scripts.
|
class |
RegressionMainTask |
class |
RunStreamTasks
Task for running several experiments modifying values of parameters.
|
class |
RunTasks
Task for running several experiments modifying values of parameters.
|
class |
WriteStreamToARFFFile
Task to output a stream to an ARFF file
|
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