TABLE 4.

The classification performance of the SVM classifier uses the leave-one-fold-out cross-validation method with different kernels (linear, Gaussian RBF, and polynomial) for different regularization parameters (C).

Parameters		Spectral feature					Histogram-Poincaré based feature					Wavelet-based feature
Kernel	C	ACC	SENS	SPEC	F1	AUC	ACC	SENS	SPEC	F1	AUC	ACC	SENS	SPEC	F1	AUC
Linear	0.01	82.91	81.20	100.00	89.40	98.20	33.09	26.40	100.00	37.23	69.60	53.81	57.00	22.00	64.09	33.60
	0.1	83.45	81.80	100.00	89.73	98.20	33.81	27.20	100.00	38.56	74.60	54.55	56.80	32.00	66.62	43.40
	1	85.64	84.20	100.00	91.11	98.20	62.18	58.40	100.00	71.31	84.20	52.00	52.60	46.00	63.93	51.00
	10	85.64	84.80	94.00	91.14	98.20	72.73	70.80	92.00	81.78	83.60	48.90	49.80	40.00	61.43	44.00
	100	85.64	84.80	94.00	91.14	98.20	70.00	68.00	90.00	79.51	82.60	48.90	49.60	42.00	61.73	45.20
RBF	0.01	78.36	77.60	86.00	85.80	93.40	34.72	28.20	100.00	38.92	81.60	54.72	56.00	42.00	67.17	55.20
	0.1	78.36	77.60	86.00	85.80	93.40	34.72	28.20	100.00	38.92	81.60	54.72	56.00	42.00	67.17	55.20
	1	78.55	77.80	86.00	85.72	92.20	34.90	28.40	100.00	39.28	81.40	54.00	55.20	42.00	66.37	53.80
	10	78.91	78.80	80.00	85.95	88.20	56.91	52.80	98.00	66.48	85.00	48.90	49.40	44.00	61.71	47.40
	100	75.45	75.60	74.00	83.50	81.80	71.45	69.00	96.00	80.36	81.60	48.90	49.40	44.00	61.71	47.40
Polynomial	0.01	88.18	87.60	94.00	92.95	98.20	27.45	20.60	96.00	30.26	58.20	68.36	72.80	24.00	71.72	37.40
	0.1	87.82	87.20	94.00	92.73	98.00	27.45	20.60	96.00	30.26	62.20	62.00	65.80	24.00	67.89	43.40
	1	86.91	86.20	94.00	92.13	97.80	29.64	23.00	96.00	34.14	67.20	48.36	49.80	34.00	59.32	38.20
	10	86.18	85.40	94.00	91.65	98.20	36.55	30.60	96.00	44.69	77.00	42.90	43.20	40.00	54.72	36.60
	100	86.00	85.20	94.00	91.48	98.20	67.09	65.20	86.00	76.34	80.80	42.91	43.20	40.00	54.72	36.60

The results reported are for the three spectral features. Best performance is obtained with spectral feature in Polynomial kernel (C $=0.01$ ): 88.18% Accuracy, 87.60% Sensitivity, 94% Specificity, 92.95% F1-score.

Bold value represents the best performance.