Table 6.

Hyperparameters evaluated in a grid search.

Method	Hyperparameters
RF	n_estimators={10, 15, 20, 25, 30, 45, 50}, min_samples_leaf={1, 2, 3, 4}, max_depth={8, 10, None}, class_weight={balanced, none}
LR	C={10−6, 5.62 × 10−5, 3.166 × 10−3, 1.77 × 10−1, 10}, class_weight={balanced, none}, penalty={L2}, random_state=1
SVM	kernel={linear, rbf}, C={10−6, 10−5, 10−4, 10−3, 10−2}class_weight={balanced and none}, random_state=1