Table 8.

Classifier Hyperparameters.

Classifier	Specification
Artificial Neural Network (MLP)	Layers: 5, Neurons in each Layer: 20, 10, 128, 256, 64, 16, 3, Loss: Categorical Cross-Entropy, Optimizer: AdaDelta, Learning Rate: Start: 1.0—Auto Reduce on Plateau Fraction: 0.8 at 2 simultaneous non decline of validation loss
XgBoost	n_estimators: 600, max_depth = 9, booster: gbtree
Random Forest	n_estimators: 1000, criterion = ‘gini’, max_depth:7, min_samples_split = 20, min_samples_leaf = 10
Support Vector Machine	Kernel = ‘rbf’, degree = 3, gamma = 0.0001 C = 1.0, tol = 0.001, cache_size = 200