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weka.FilteredClassifier_MultiSearch_MultilayerPerceptron

weka.FilteredClassifier_MultiSearch_MultilayerPerceptron

Visibility: public Uploaded 14-06-2016 by Jan van Rijn Weka_3.7.13 94 runs
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  • Verified_Supervised_Classification weka weka_3.7.13
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Weka implementation of FilteredClassifier

Components

Wweka.MultiSearch_MultilayerPerceptron(1)Full name of base classifier. (default: weka.classifiers.trees.J48)

Parameters

-do-not-check-capabilitiesIf set, classifier capabilities are not checked before classifier is built (use with caution).
-doNotMakeSplitPointActualValueDo not make split point actual value.
ALaplace smoothing for predicted probabilities.
BUse binary splits only.
CSet confidence threshold for pruning. (default 0.25)
DOutput binary attributes for discretized attributes.
EUse better encoding of split point for MDL.
FFull class name of filter to use, followed by filter options. eg: "weka.filters.unsupervised.attribute.Remove -V -R 1,2"default: weka.filters.supervised.attribute.Discretize -R first-last -precision 6
JDo not use MDL correction for info gain on numeric attributes.
KUse Kononenko's MDL criterion.
LDo not clean up after the tree has been built.
MSet minimum number of instances per leaf. (default 2)
NSet number of folds for reduced error pruning. One fold is used as pruning set. (default 3)
ODo not collapse tree.
QSeed for random data shuffling (default 1).
RUse reduced error pruning.
SDo not perform subtree raising.
UUse unpruned tree.
VInvert matching sense of column indexes.
WFull name of base classifier. (default: weka.classifiers.trees.J48)default: weka.classifiers.meta.MultiSearch
YUse bin numbers rather than ranges for discretized attributes.
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
precisionPrecision for bin boundary labels. (default = 6 decimal places).

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