Table 2.

Performance of HM-SVM based method with and without order profile propensities.

Dataset	Method	Sp %	Sn %	F1 %	Acc %	MCC	AUC %
Heterocomplex I	HM-SVM 1a	44.9	56.0	49.8	68.3	0.274	69.5
	HM-SVM 2b	52.4	73.5	61.2	73.8	0.436	81.4
Homocomplex I	HM-SVM 1	45.4	60.0	51.70	69.7	0.309	72.2
	HM-SVM 2	54.5	74.6	62.9	76.3	0.474	83.6
Mix I	HM-SVM 1	45.5	58.0	51.0	69.4	0.297	71.2
	HM-SVM 2	53.5	74.0	62.1	75.0	0.455	82.5
Heterocomplex II	HM-SVM 1	54.0	56.7	55.3	68.0	0.305	70.7
	HM-SVM 2	60.8	71.7	65.8	74.0	0.454	81.2
Homocomplex II	HM-SVM 1	53.3	60.1	56.5	70.1	0.340	73.4
	HM-SVM 2	61.1	73.8	66.8	76.4	0.493	83.7
Mix II	HM-SVM 1	53.6	58.6	56.0	69.3	0.326	72.4
	HM-SVM 2	61.0	72.7	66.3	75.2	0.474	82.4

^aResults of HM-SVM 1 on the six data sets are obtained from [13]. HM-SVM 1 represents the HM-SVM predictor with the basic feature set using PSSM and ASA features; ^bHM-SVM 2 represents the HM-SVM predictor with the feature set using PSSM, ASA, and order profile propensity features.