Table 3.

Machine learning models’ settings.

Models	Parameters	Models	Parameters
NB	useKernelEstimator: False useSupervisedDiscretization: True	RotF	classifier: RF numberOfGroups: True projectionFilter: PrincipalComponents
LR	ridge = ${10}^{-8}$ useConjugateGradientDescent: True	J48	reducedErrorPruning: False savelnstanceData: True useMDLCorrection: True, subtreeRaising: True binarySplits = True, collapseTree = True
MLP	learning rate = 0.1 momentum = 0.2 training time = 200	Stacking	classifiers: RF and NB metaClassifier: LR
KNN	K=3 Search Algorithm: LinearNNSearch with Euclidean cross-validate = True	Voting	classifiers: RF and NB combinationRule: average of probabilities
RF	breakTiesRadomly: True numIterations = 500 storeOutOfBagPredictions: True	Bagging	classifiers: RF printClassifiers: True storeOutOfBagPredictions: True