Table 9.

Machine Learning Models’ Settings.

Models	Parameters
NB	useKernelEstimator: False useSupervisedDiscretization: True
LR	ridge = ${10}^{-8}$ useConjugateGradientDescent: True
MLP	learning rate = 0.1 momentum = 0.2 training time = 200
kNN	k = 3 Search Algorithm: LinearNNSearch with Euclidean cross-validate = True
RF	breakTiesRadomly: True numIterations = 500 storeOutOfBagPredictions: True
RotF	classifier: Random Forest numberOfGroups: True projectionFilter: PrincipalComponents
AdaBoostM1	classifier: Random Forest resume: True useResampling: True
Stacking	classifiers: Random Forest and Naive Bayes metaClassifier: Logistic Regression
Voting	classifiers: Random Forest and Naive Bayes combinationRule: average of probabilities
Bagging	classifiers: Random Forest printClassifiers: True storeOutOfBagPredictions: True