Visibility: public Uploaded 18-02-2015 by Joaquin Vanschoren Weka_3.7.12 5814 runs
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  • study_1 study_41 Verified_Learning_Curve,Verified_Supervised_Classification weka weka_3.7.12
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Tin Kam Ho (1998). The Random Subspace Method for Constructing Decision Forests. IEEE Transactions on Pattern Analysis and Machine Intelligence. 20(8):832-844. URL http://citeseer.ist.psu.edu/ho98random.html.


Wweka.REPTree(9)Full name of base classifier. (default: weka.classifiers.trees.REPTree)


-do-not-check-capabilitiesIf set, classifier capabilities are not checked before classifier is built (use with caution).
INumber of iterations. (default 10)default: 10
LMaximum tree depth (default -1, no maximum)
MSet minimum number of instances per leaf (default 2).
NNumber of folds for reduced error pruning (default 3).
PSize of each subspace: < 1: percentage of the number of attributes >=1: absolute number of attributesdefault: 0.5
RSpread initial count over all class values (i.e. don't use 1 per value)
SRandom number seed. (default 1)default: 1
VSet minimum numeric class variance proportion of train variance for split (default 1e-3).
WFull name of base classifier. (default: weka.classifiers.trees.REPTree)default: weka.classifiers.trees.REPTree
num-slotsNumber of execution slots. (default 1 - i.e. no parallelism) (use 0 to auto-detect number of cores)default: 1
output-debug-infoIf set, classifier is run in debug mode and may output additional info to the console


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