Table 5 Configurations of classifiers

Random forest

Number of trees in the forest = 50, maximum depth of each tree = 20, the minimum number of samples to split each node = 8

XGBoost

Learning rate = 0.3, maximum depth of each tree = 6, minimum loss reduction to split each node = 1, regularization term on weights = 20, subsample ratio of columns for each tree = 0.5

Decision tree

Maximum depth = 12

K-nearest neighbor

Number of k = 7

Support vector machine

Kernel = Radius basis function, C = 1, Gamma (γ) = 0.001

Logistic regression

Batch size = 100, Debug = True, Standardize attribute = True, Maximum number of iterations to perform = 100, Ridge value in the likelihood = 1.0E-8, conjugate gradient descent = True