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weka.HoeffdingTree

weka.HoeffdingTree

Visibility: public Uploaded 04-04-2014 by Jan van Rijn Weka_3.7.10 49 runs
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  • Verified_Learning_Curve,Verified_Supervised_Classification study_237
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Geoff Hulten, Laurie Spencer, Pedro Domingos: Mining time-changing data streams. In: ACM SIGKDD Intl. Conf. on Knowledge Discovery and Data Mining, 97-106, 2001.

Parameters

EThe allowable error in a split decision - values closer to zero will take longer to decide (default = 1e-7)default: 1.0E-7
GGrace period - the number of instances a leaf should observe between split attempts (default = 200)default: 200.0
HThreshold below which a split will be forced to break ties (default = 0.05)default: 0.05
LThe leaf prediction strategy to use. 0 = majority class, 1 = naive Bayes, 2 = naive Bayes adaptive. (default = 2)default: 2
MMinimum fraction of weight required down at least two branches for info gain splitting (default = 0.01)default: 0.01
NThe number of instances (weight) a leaf should observe before allowing naive Bayes to make predictions (NB or NB adaptive only) (default = 0)default: 0.0
PPrint leaf models when using naive Bayes at the leaves.
SThe splitting criterion to use. 0 = Gini, 1 = Info gain (default = 1)default: 1

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