Table 9.

Melanoma detection performance using texture-based weighted graph features. The skin lesion feature descriptors include local features (C), global features (G), local and global features (C+G), graph Fourier transform features (GFT), local, global and GFT features (C+G+GFT), local, global and conventional features (C+G+Conv), GFT and conventional features (GFT+Conv) and the combination of all features (All). The performance metrics for each classifier are the accuracy (AC), specificity (SP) and sensitivity (SN)

		C	G	C+G	GFT	C+G+GFT	C+G+Conv	GFT+Conv	All
SVM (RBF)	AC	59.34	55.36	58.65>	52.08	58.82	87.54	89.45	88.41
	AUC	61.76	54.88	58.66	51.84	60.38	98.28	98.79	97.9
	SN	57.79	49.13	52.94	55.36	58.82	98.96	99.31	99.31
	SP	65.74	68.86	66.44	55.71	64.71	78.89	79.93	78.2
SVM (Sigmoid)		57.96	55.54	55.02	52.42	57.96	77.85	75.78	74.05
	AUC	50.04	55.78	51.89	53.26	45.97	82.94	87.55	79.84
	SN	68.51	43.25	64.36	56.4	67.82	87.54	92.73	84.43
	SP	49.13	84.08	51.56	54.67	54.67	68.17	64.71	65.05
SVM (Poly)	AC	54.5	50.35	54.67	47.58	51.9	93.43	89.62	94.29
	AUC	50.04	55.78	51.89	53.26	45.97	82.94	87.55	79.84
	SN	16.26	2.076	19.38	9.689	10.73	95.5	96.19	93.77
	SP	94.81	100.0	92.73	92.04	95.5	94.12	84.43	95.16
KNN	AC	52.94	53.98	55.19	55.71	54.15	84.43	83.04	83.91
	AUC	53.12	53.53	55.82	56.64	54.57	94.75	96.51	94.41
	SN	33.56	49.13	39.1	64.01	44.64	97.92	100.0	98.27
	SP	75.09	58.82	71.97	54.67	67.13	73.7	67.82	70.24
MLP	AC	56.92	54.33	56.57	53.29	56.4	89.79	90.48	89.45
	AUC	59.93	57.79	60.26	52.8	59.47	98.68	99.25	98.37
	SN	51.9	54.67	52.25	51.21	48.44	99.65	99.65	98.62
	SP	66.44	60.9	65.74	56.06	67.82	82.35	81.66	81.66
RF	AC	50.35	53.63	51.21	53.46	51.21	97.23	98.44	97.75
	AUC	59.01	55.41	58.61	58.76	60.68	99.86	99.89	99.89
	SN	2.768	26.64	2.422	12.46	2.768	98.96	100.0	99.31
	SP	100.0	85.12	100.0	96.89	100.0	96.19	96.89	97.23