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weka.CostSensitiveClassifier_FilteredClassifier_SMO_PolyKernel

weka.CostSensitiveClassifier_FilteredClassifier_SMO_PolyKernel

Visibility: public Uploaded 17-04-2017 by Wouter Nuijten Weka_3.8.1 6 runs
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  • Verified_Supervised_Classification weka weka_3.8.1
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Weka implementation of CostSensitiveClassifier

Components

Wweka.FilteredClassifier_SMO_PolyKernel(1)Full name of base classifier. (default: weka.classifiers.rules.ZeroR)

Parameters

-do-not-check-capabilitiesIf set, classifier capabilities are not checked before classifier is built (use with caution).
CFile name of a cost matrix to use. If this is not supplied, a cost matrix will be loaded on demand. The name of the on-demand file is the relation name of the training data plus ".cost", and the path to the on-demand file is specified with the -N option.
MMinimize expected misclassification cost. Default is to reweight training instances according to costs per class
NName of a directory to search for cost files when loading costs on demand (default current directory).default: C:\Program Files\Weka-3-8
SRandom number seed. (default 1)default: 1
WFull name of base classifier. (default: weka.classifiers.rules.ZeroR)default: weka.classifiers.meta.FilteredClassifier
batch-sizeThe desired batch size for batch prediction (default 100).
cost-matrixThe cost matrix in Matlab single line format.
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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