Table 3.

Hyperparameters value of the optimal ML models

	KNN	DT	SVM		SLP	RF
Patient test	K	mSL	S	C	neurons	mSL	nFeats	nTrees
2	11	11	21.92	990.51	55	51	5	100
4	15	77	16.06	994.56	40	50	13	150
6	11	23	3.34	39.83	50	50	12	50
7	13	79	0.14	0.13	55	50	15	250
9	11	22	0.81	3.73	60	50	15	100
10	37	20	1.80	12.26	55	50	13	150

K is the number of neighbors, mSL is the minimum samples at each leaf node, S is a scaling factor, C is the regularization parameter, neurons is the number of neurons in the hidden layer, nFeats is the number of features and nTrees is the number of trees