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Table 4 Weka classification parameters

From: Multi-method approach to wellness predictive modeling

Classifier Parameter name Parameter value
MLP hiddenLayers 22
learningRate 0.3
momentum 0.2
trainingTime 500
validationSetSize 0
validationThreshold 20
Rbf network maxIts −1
minStdDev 0.1
numClusters 1
ridge 1E−8
J48 confidenceFactor 0.25
minNumObj 2
NB None  
BN estimator SimpleEstimator
searchAlgorithm K2
SMO kernel PolyKernel
tolerance 0.001
Bagging classifier J48
bags 10
bagsize 100 %
AdaboostM1 classifier NB
iterations 10
RF trees 2500
features 4