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weka.KernelLogisticRegression_PolyKernel

weka.KernelLogisticRegression_PolyKernel

Visibility: public Uploaded 07-10-2014 by Felicia West Weka_3.7.12-SNAPSHOT 0 runs
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Weka implementation of KernelLogisticRegression

Components

Kweka.PolyKernel(4)The Kernel to use. (default: weka.classifiers.functions.supportVector.PolyKernel)

Parameters

-do-not-check-capabilitiesIf set, classifier capabilities are not checked before classifier is built (use with caution).
CThe size of the cache (a prime number), 0 for full cache and -1 to turn it off. (default: 250007)
EThe number of threads to use, which should be >= size of thread pool. (default 1)default: 1
GUse conjugate gradient descent instead of BFGS.
KThe Kernel to use. (default: weka.classifiers.functions.supportVector.PolyKernel)default: weka.classifiers.functions.supportVector.PolyKernel
LThe lambda penalty parameter. (default 0.01)default: 0.01
PThe size of the thread pool, for example, the number of cores in the CPU. (default 1)default: 1
SRandom number seed. (default 1)default: 1
no-checksTurns off all checks - use with caution! (default: checks on)
output-debug-infoIf set, classifier is run in debug mode and may output additional info to the console

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