Table 4.

Over Enhancers strength prediction dataset and its independent test set performance comparison of Proposed and existing frameworks in terms of 4 evaluation measures

		5-Fold					Indepencent
	framework	ACC	Sn	Sp	MCC		ACC	Sn	Sp	MCC
Weak/ Strong Enhancer	EnhancerPred [31]	62.06	62. 67	61.46	0.24		55	45	65	0.1021
	iEnhancer-2L [33]	61.93	62.21	61.82	0.24		60.5	47	74	0.2181
	iEnhancer-EL [43]	65.03	69	61.05	0.31		61	54	68	0.2222
	iEnhancer-Deep [16]	80.86	83.57	78.16	0.62		61	73	49	0.2266
	iEnhancer-XG [45]	66.74	74.94	58.55	0.33		63.5	70	57	0.272
	iEnhancer-EBLSTM [74]	-	-	-	-		65.8	81.2	53.6	0.324
	iEnhancer-ECNN [75]	-	-	-	-		67.8	79.1	56.4	0.368
	tan2019ensemble [44]	58.96	79.65	38.28	0.19		-	-	-	-
	Tan et al. Enhancer [44]	59	80	38	0.2		68.49	0.83	0.46	0.31
	iEnhancer-DSNet [2]	63	63	67	0.26		83	83	67	0.70
	Rank-GAN [51]	69.7	70.68	68.89	0.3954		69.7	70.68	68.89	0.3954
	iEnhacner-BERT [47]	65.3	-	-	0.31		70.1			0.401
	iEnhancer-5Step [37]	68.1	75.53	60.8	0.37		-	-	-	-
	Enhancer-RD [36]	-	-	-	-		70.5	84	57	0.426
	iEnhancer-GAN [36]	-	-	-	-		74.9	96.1	53.7	0.505
	iEnhancer-CNN [65]	76.43	73.64	76.8	0.45		75	65.25	76.1	0.3232
	iEnhancer-DCLA [52]	83.3	89.27	77.33	0.6736		78	87	69	0.5693
	iEnhancer-MRBF [53]	76.95	77.23	79.69	0.5419		83.50	100.00	67.00	0.7098
	Proposed	90	90	89.6	0.8		87.5	87.3	75	0.774