Table 3.

Performance comparison of MLAFP-XN with existing proposed methods on similar datasets.

Dataset name	Proposed model	Accuracy (%)	References
Antifp_DS1	AntiFP	87.29	[9]
	AFPDeep	90.21	[10]
	iAMPCN	69.59	[41]
	AFPtransferPred	48.97	[42]
	AFP-MFL	94.40	[8]
	DeepAFP	92.44	[14]
	MLAFP-XN	97.93	This study
Antifp_DS2	AntiFP	90.21	[9]
	AFPDeep	94.67	[10]
	iAMPCN	84.19	[41]
	AFPtransferPred	66.32	[42]
	AFP-MFL	96.84	[8]
	DeepAFP	96.05	[14]
	Deep-AFPpred	56.49	[47]
	MLAFP-XN	99.47	This study
Antifp_Main	AntiFP	84.98	[9]
	AFPDeep	91.05	[10]
	iAMPCN	79.35	[41]
	AFPtransferPred	58.35	[42]
	AFP-MFL	95.84	[8]
	DeepAFP	93.29	[14]
	Deep-AFPpred	51.45	[47]
	MLAFP-XN	99.48	This study
Other datasets	Deep-AFPpred	94.27	[47]
	PhytoAFP	94.4	[48]