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weka.AdaBoostM1_SMO_PolyKernel

weka.AdaBoostM1_SMO_PolyKernel

Visibility: public Uploaded 13-04-2017 by Daan Dinkla Weka_3.9.1 0 runs
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Yoav Freund, Robert E. Schapire: Experiments with a new boosting algorithm. In: Thirteenth International Conference on Machine Learning, San Francisco, 148-156, 1996.

Components

Wweka.SMO_PolyKernel(16)Full name of base classifier. (default: weka.classifiers.trees.DecisionStump)

Parameters

-do-not-check-capabilitiesIf set, classifier capabilities are not checked before classifier is built (use with caution).
INumber of iterations. (current value 10)default: 10
PPercentage of weight mass to base training on. (default 100, reduce to around 90 speed up)default: 100
QUse resampling for boosting.
SRandom number seed. (default 1)default: 1
WFull name of base classifier. (default: weka.classifiers.trees.DecisionStump)default: weka.classifiers.functions.SMO
batch-sizeThe desired batch size for batch prediction (default 100).
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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