Predictions of Apoptosis Proteins by Integrating Different Features Based on Improving Pseudo-Position-Specific Scoring Matrix

Table 2

The contribution of two feature submodels for the final overall accuracy (%).

Datasets	Index	IM-Psepssm	T1-IM-PSSM	T2-IM-PSSM	T3-IIM-PSSM	BID-CC	BIM-PSSM
ZD98	Sn	95.92	93.26	93.84	88.0	93	94.41
	Sp	98.59	97.85	98.14	96.49	97.60	98.27
	F-m	96.59	94.77	95.97	94.11	96.19	97.88
	Mcc	93.82	90.41	92.0	86.28	91.52	94.32
	G-mean	97.23	95.48	95.90	91.81	95.20	96.24
	OA	95.91	93.87	94.89	90.81	93.87	95.91
ZW225	Sn	83.80	79.67	78.03	75.87	81	84.55
	Sp	95.28	93.82	93.34	92.68	94.4	95.52
	F-m	91.36	88.24	87.39	87.24	89.32	90.34
	Mcc	81.00	75.27	73.36	71.81	77.36	80.69
	G-mean	89.21	86.29	85.11	83.55	87.29	89.79
	OA	86.66	82.66	81.33	80	84.44	87.55
CL317	Sn	88.21	88.64	89.25	81.64	87.54	88.84
	Sp	97.88	97.76	97.89	96.79	97.85	98
	F-m	93.97	92.91	93.93	93.09	93.80	95.42
	Mcc	87.22	86.38	87.66	82.18	86.71	88.88
	G-mean	92.87	93.06	93.44	88.56	92.45	93.22
	OA	90.22	89.58	90.22	86.12	90.22	91.48