public class LimAttHoeffdingTree extends HoeffdingTree
@article{BifetFHP10, author = {Albert Bifet and Eibe Frank and Geoffrey Holmes and Bernhard Pfahringer}, title = {Accurate Ensembles for Data Streams: Combining Restricted Hoeffding Trees using Stacking}, journal = {Journal of Machine Learning Research - Proceedings Track}, volume = {13}, year = {2010}, pages = {225-240} }
Modifier and Type | Class and Description |
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static class |
LimAttHoeffdingTree.LearningNodeNB |
static class |
LimAttHoeffdingTree.LearningNodeNBAdaptive |
static class |
LimAttHoeffdingTree.LimAttLearningNode |
HoeffdingTree.ActiveLearningNode, HoeffdingTree.FoundNode, HoeffdingTree.InactiveLearningNode, HoeffdingTree.LearningNode, HoeffdingTree.Node, HoeffdingTree.SplitNode
Modifier and Type | Field and Description |
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protected int[] |
listAttributes |
activeLeafByteSizeEstimate, activeLeafNodeCount, binarySplitsOption, byteSizeEstimateOverheadFraction, decisionNodeCount, gracePeriodOption, growthAllowed, inactiveLeafByteSizeEstimate, inactiveLeafNodeCount, leafpredictionOption, maxByteSizeOption, memoryEstimatePeriodOption, nbThresholdOption, nominalEstimatorOption, noPrePruneOption, numericEstimatorOption, removePoorAttsOption, splitConfidenceOption, splitCriterionOption, stopMemManagementOption, tieThresholdOption, treeRoot
classifierRandom, modelContext, randomSeed, randomSeedOption, trainingWeightSeenByModel
config
Constructor and Description |
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LimAttHoeffdingTree() |
Modifier and Type | Method and Description |
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String |
getPurposeString()
Dictionary with option texts and objects
|
boolean |
isRandomizable()
Gets whether this learner needs a random seed.
|
protected HoeffdingTree.LearningNode |
newLearningNode(double[] initialClassObservations) |
void |
setlistAttributes(int[] list) |
activateLearningNode, attemptToSplit, calcByteSize, computeHoeffdingBound, deactivateAllLeaves, deactivateLearningNode, enforceTrackerLimit, estimateModelByteSizes, findLearningNodes, findLearningNodes, getModelDescription, getModelMeasurementsImpl, getVotesForInstance, measureByteSize, measureTreeDepth, newLearningNode, newNominalClassObserver, newNumericClassObserver, newSplitNode, newSplitNode, resetLearningImpl, trainOnInstanceImpl
contextIsCompatible, copy, correctlyClassifies, getAttributeNameString, getAWTRenderer, getClassLabelString, getClassNameString, getDescription, getModel, getModelContext, getModelMeasurements, getNominalValueString, getPredictionForInstance, getPredictionForInstance, getSubClassifiers, getSublearners, getVotesForInstance, modelAttIndexToInstanceAttIndex, modelAttIndexToInstanceAttIndex, prepareForUseImpl, resetLearning, setModelContext, setRandomSeed, trainingHasStarted, trainingWeightSeenByModel, trainOnInstance, trainOnInstance
getCLICreationString, getOptions, getPreparedClassOption, prepareClassOptions, prepareForUse, prepareForUse
copy, measureByteSize, toString
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait
getCLICreationString, getOptions, prepareForUse, prepareForUse
public String getPurposeString()
AbstractOptionHandler
getPurposeString
in interface OptionHandler
getPurposeString
in class HoeffdingTree
public void setlistAttributes(int[] list)
protected HoeffdingTree.LearningNode newLearningNode(double[] initialClassObservations)
newLearningNode
in class HoeffdingTree
public boolean isRandomizable()
Learner
isRandomizable
in interface Learner<Example<Instance>>
isRandomizable
in class HoeffdingTree
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