Visibility: public Uploaded 12-04-2017 by Freek Rooks Weka_3.8.1 277 runs
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  • Verified_Supervised_Classification weka weka_3.8.1
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Weka implementation of FilteredClassifier


Wweka.SMO_PolyKernel(15)Full name of base classifier. (default: weka.classifiers.trees.J48)


-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.functions.SMO
YUse bin numbers rather than ranges for discretized attributes.
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
precisionPrecision for bin boundary labels. (default = 6 decimal places).


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