Table 5.

Comparison to existing methods via 5-fold Cross-Validation.

Datasets	Methods	AUPR	AUC
Pauwels	Pauwels's methoda	0.389 ± N/A	0.897 ± N/A
	Liu's methoda	0.345 ± N/A	0.920 ± N/A
	Cheng's methoda	0.588 ± N/A	0.922 ± N/A
	RBMBMa [26]	0.612 ± N/A	0.941 ± N/A
	INBMa [26]	0.641 ± N/A	0.934 ± N/A
	Ensemble modela [26]	0.660 ± N/A	0.949 ± N/A
	CMFb	0.646 ± 0.007	0.939 ± 0.005
	GRMFb	0.643 ± 0.006	0.937 ± 0.005
	NRLMFb	0.654 ± 0.005	0.954 ± 0.005
	LGCb	0.668 ± 0.008	0.952 ± 0.007
	Our method	0.677 ± 0.004	0.943 ± 0.003
Mizutani	Mizutani's methoda	0.412 ± N/A	0.890 ± N/A
	Liu's methoda	0.366 ± N/A	0.918 ± N/A
	Cheng's methoda	0.599 ± N/A	0.923 ± N/A
	RBMBMa [26]	0.619 ± N/A	0.939 ± N/A
	INBMa [26]	0.646 ± N/A	0.932 ± N/A
	Ensemble modela [26]	0.666 ± N/A	0.946 ± N/A
	CMFb	0.645 ± 0.005	0.938 ± 0.006
	GRMFb	0.646 ± 0.007	0.937 ± 0.007
	NRLMFb	0.660 ± 0.006	0.950 ± 0.005
	LGCb	0.673 ± 0.007	0.948 ± 0.007
	Our method	0.685 ± 0.006	0.941 ± 0.008
Liu	Liu's methoda	0.278 ± N/A	0.907 ± N/A
	Cheng's methoda	0.592 ± N/A	0.922 ± N/A
	RBMBMa [26]	0.616 ± N/A	0.941 ± N/A
	INBMa [26]	0.641 ± N/A	0.934 ± N/A
	Ensemble modela [26]	0.661 ± N/A	0.948 ± N/A
	CMFb	0.649 ± 0.006	0.938 ± 0.005
	GRMFb	0.650 ± 0.007	0.938 ± 0.008
	NRLMFb	0.656 ± 0.005	0.953 ± 0.006
	LGCb	0.670 ± 0.008	0.951 ± 0.007
	Our method	0.680 ± 0.005	0.943 ± 0.006

^aResults are derived from [26]. ^bResults are derived from [18].