public class HoeffdingAdaptiveTreeClassifLeaves extends HoeffdingAdaptiveTree
used in the data stream configuration in J. P. Barddal, H. M.
Gomes, F. Enembreck, B. Pfahringer & A. Bifet. ON DYNAMIC FEATURE WEIGHTING
FOR FEATURE DRIFTING DATA STREAMS. In European Conference on Machine Learning
and Principles and Practice of Knowledge Discovery (ECML/PKDD'16). 2016.
,
Serialized FormModifier and Type | Class and Description |
---|---|
class |
HoeffdingAdaptiveTreeClassifLeaves.LearningNodeHATClassifier |
HoeffdingAdaptiveTree.AdaLearningNode, HoeffdingAdaptiveTree.AdaSplitNode, HoeffdingAdaptiveTree.NewNode
HoeffdingTree.ActiveLearningNode, HoeffdingTree.FoundNode, HoeffdingTree.InactiveLearningNode, HoeffdingTree.LearningNode, HoeffdingTree.LearningNodeNB, HoeffdingTree.LearningNodeNBAdaptive, HoeffdingTree.Node, HoeffdingTree.SplitNode
Modifier and Type | Field and Description |
---|---|
ClassOption |
leaveLearnerOption |
alternateTrees, errorWidthOption, fDeltaOption, prunedAlternateTrees, switchedAlternateTrees
activeLeafByteSizeEstimate, activeLeafNodeCount, binarySplitsOption, byteSizeEstimateOverheadFraction, decisionNodeCount, gracePeriodOption, growthAllowed, inactiveLeafByteSizeEstimate, inactiveLeafNodeCount, leafpredictionOption, maxByteSizeOption, maxTreeDepth, memoryEstimatePeriodOption, nbThresholdOption, nominalEstimatorOption, noPrePruneOption, numericEstimatorOption, removePoorAttsOption, splitConfidenceOption, splitCriterionOption, stopMemManagementOption, tieThresholdOption, treeRoot
classifierRandom, downSampleRatio, modelContext, randomSeed, randomSeedOption, trainingWeightSeenByModel
config
Constructor and Description |
---|
HoeffdingAdaptiveTreeClassifLeaves() |
Modifier and Type | Method and Description |
---|---|
protected void |
attemptToSplit(HoeffdingTree.ActiveLearningNode node,
HoeffdingTree.SplitNode parent,
int parentIndex) |
protected HoeffdingTree.LearningNode |
newLearningNode(double[] initialClassObservations) |
protected HoeffdingTree.LearningNode |
newLearningNode(double[] initialClassObservations,
Classifier cl) |
filterInstanceToLeaves, getPurposeString, getVotesForInstance, newSplitNode, newSplitNode, trainOnInstanceImpl
activateLearningNode, calcByteSize, computeHoeffdingBound, deactivateAllLeaves, deactivateLearningNode, enforceTrackerLimit, estimateModelByteSizes, findLearningNodes, findLearningNodes, getModelDescription, getModelMeasurementsImpl, isRandomizable, measureByteSize, measureTreeDepth, newLearningNode, newNominalClassObserver, newNumericClassObserver, resetLearningImpl
contextIsCompatible, copy, correctlyClassifies, getAttributeNameString, getAWTRenderer, getClassLabelString, getClassNameString, getDescription, getDownSampleRatio, getModel, getModelContext, getModelMeasurements, getNominalValueString, getPredictionForInstance, getPredictionForInstance, getSubClassifiers, getSublearners, getVotesForInstance, modelAttIndexToInstanceAttIndex, modelAttIndexToInstanceAttIndex, prepareForUseImpl, resetLearning, setModelContext, setRandomSeed, trainingHasStarted, trainingWeightSeenByModel, trainOnInstance, trainOnInstance, updateDownSampleRatio
getCLICreationString, getOptions, getPreparedClassOption, prepareClassOptions, prepareForUse, prepareForUse
copy, measureByteSize, toString
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait
getCLICreationString, getOptions, prepareForUse, prepareForUse
public ClassOption leaveLearnerOption
protected HoeffdingTree.LearningNode newLearningNode(double[] initialClassObservations)
newLearningNode
in class HoeffdingAdaptiveTree
protected HoeffdingTree.LearningNode newLearningNode(double[] initialClassObservations, Classifier cl)
protected void attemptToSplit(HoeffdingTree.ActiveLearningNode node, HoeffdingTree.SplitNode parent, int parentIndex)
attemptToSplit
in class HoeffdingTree
Copyright © 2019 University of Waikato, Hamilton, NZ. All Rights Reserved.