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weka.RandomCommittee_MultilayerPerceptron

weka.RandomCommittee_MultilayerPerceptron

Visibility: public Uploaded 25-07-2017 by Miguel Cachada Weka_3.8.1 0 runs
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Weka implementation of RandomCommittee

Components

Wweka.MultilayerPerceptron(8)Full name of base classifier. (default: weka.classifiers.trees.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.
INumber of iterations. (current value 10)default: 10
KNumber of attributes to randomly investigate. (default 0) (<1 = int(log_2(#predictors)+1)).
MSet minimum number of instances per leaf. (default 1)
NNumber of folds for backfitting (default 0, no backfitting).
SRandom number seed. (default 1)default: 1
UAllow unclassified instances.
VSet minimum numeric class variance proportion of train variance for split (default 1e-3).
WFull name of base classifier. (default: weka.classifiers.trees.RandomTree)default: weka.classifiers.functions.MultilayerPerceptron
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).
num-slotsNumber of execution slots. (default 1 - i.e. no parallelism) (use 0 to auto-detect number of cores)default: 1
output-debug-infoIf set, classifier is run in debug mode and may output additional info to the console

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