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moa.HoeffdingTree

moa.HoeffdingTree

Visibility: public Uploaded 18-12-2015 by Jan van Rijn Moa_14.04_April_2014 0 runs
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Moa implementation of HoeffdingTree

Parameters

bbinarySplits: Only allow binary splits.default: false
csplitConfidence: The allowable error in split decision, values closer to 0 will take longer to decide.default: 1.0E-7
dnominalEstimator: Nominal estimator to use.default: NominalAttributeClassObserver
ememoryEstimatePeriod: How many instances between memory consumption checks.default: 1000000
ggracePeriod: The number of instances a leaf should observe between split attempts.default: 200
lleafprediction: Leaf prediction to use.default: NBAdaptive
mmaxByteSize: Maximum memory consumed by the tree.default: 33554432
nnumericEstimator: Numeric estimator to use.default: GaussianNumericAttributeClassObserver
pnoPrePrune: Disable pre-pruning.default: false
qnbThreshold: The number of instances a leaf should observe before permitting Naive Bayes.default: 0
rremovePoorAtts: Disable poor attributes.default: false
ssplitCriterion: Split criterion to use.default: InfoGainSplitCriterion
ttieThreshold: Threshold below which a split will be forced to break ties.default: 0.05
zstopMemManagement: Stop growing as soon as memory limit is hit.default: false

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