Table 3. Summary of the Different Hyperparameters for the Different ML Methods.

hyperparameters	range	optimum values
Decision Tree
max_depth	5–25	9
max_features	‘log2’	‘auto’
random_state	1–100	1
Random Forests
max_depth	5–25	23
max_features	‘log2′, ‘auto’	‘log2’
random_state	1–100	1
‘n_estimators’	1–200	50
Support Vector Machine
lambda =	1 × 10–6 to 0.1	1 × 10–5
epsilon	1 × 10–6 to 1	0.00001
kernel option	1–10	3.5
verbose	1	1
C	50–2000	400
kernel	‘poly’, ‘Gaussian’	‘Gaussian’