Table 3.

Performance comparison of proposed features with AAC, DPC, PSSM, and the combined features with highest performance values for each class highlighted in bold

	Cross-validation data
Feature types	Acc (%)	Spec (%)	Sen (%)	MCC
AAC	60.69 ± 12.13	59.61 ± 15.82	68.01 ± 19.77	0.24 ± 0.09
DPC	70.42 ± 13.97	72.89 ± 17.91	51.67 ± 20.14	0.24 ± 0.13
AAC-DPC	86.48 ± 5.82	88.83 ± 8.04	69.34 ± 16.62	0.53 ± 0.08
PSSM	89.57 ± 6.68	91.88 ± 5.73	73.34 ± 18.33	0.61 ± 0.16
PSSM-AAC	91.17 ± 3.18	93.19 ± 4.11	76.34 ± 12.91	0.66 ± 0.1
PSSM-DPC	91.25 ± 3.29	93.85 ± 4.58	72.34 ± 12.58	0.64 ± 0.09
PSSM-DPC-AAC	91.25 ± 2.84	93.67 ± 3.85	73.67 ± 14.45	0.64 ± 0.1
Proposed features	95.82 ± 1.67	97.59 ± 2.15	83.67 ± 7.45	0.83 ± 0.06
	Independent data
Feature types	Acc (%)	Spec (%)	Sen (%)	MCC
AAC	46.92 ± 25.59	42.37 ± 33.15	81.25 ± 34.49	0.20 ± 0.07
DPC	82.05 ± 23.71	84.63 ± 29.06	62.75 ± 39.92	0.46 ± 0.28
AAC-DPC	93.65 ± 2.66	94.95 ± 3.26	83.75 ± 9.59	0.73 ± 0.09
PSSM	94.85 ± 2.82	97.56 ± 2.85	74.5 ± 28.35	0.72 ± 0.26
PSSM-AAC	95.77 ± 1.45	97.42 ± 2.14	83.25 ± 11.31	0.81 ± 0.06
PSSM-DPC	95.94 ± 1.33	97.81 ± 1.49	82 ± 8.8	0.81 ± 0.07
PSSM-DPC-AAC	95.14 ± 2.02	96.77 ± 2.48	83 ± 9.7	0.78 ± 0.08
Proposed features	96.49 ± 4.34	98 ± 5.27	85 ± 17.48	0.86 ± 0.13

(Each result is reported in format: m ± d, where m is the mean and d is the standard deviation across the ten runs)