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weka.RandomTree

weka.RandomTree

Visibility: public Uploaded 30-03-2017 by Daan Dinkla Weka_3.8.1 4 runs
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  • Verified_Supervised_Classification weka weka_3.8.1
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Weka implementation of RandomTree

Parameters

-do-not-check-capabilitiesIf set, classifier capabilities are not checked before classifier is built (use with caution).
BBreak ties randomly when several attributes look equally good.
KNumber of attributes to randomly investigate. (default 0) (<1 = int(log_2(#predictors)+1)).default: 0
MSet minimum number of instances per leaf. (default 1)default: 1.0
NNumber of folds for backfitting (default 0, no backfitting).
SSeed for random number generator. (default 1)default: 1
UAllow unclassified instances.
VSet minimum numeric class variance proportion of train variance for split (default 1e-3).default: 0.001
batch-sizeThe desired batch size for batch prediction (default 100).
depthThe maximum depth of the tree, 0 for unlimited. (default 0)
num-decimal-placesThe number of decimal places for the output of numbers in the model (default 2).
output-debug-infoIf set, classifier is run in debug mode and may output additional info to the console

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