Table 4.

Overall performance analysis of the proposed ACV-DHOA-CNN-EC over classifier

Methods	RELM [2]	CNNBCN [4]	CapNet [5]	DAE-JOA [7]	Proposed ACV-DHOA-CNN-EC
Accuracy	0.92885	0.90909	0.90514	0.92885	0.95257
Sensitivity	0.95	0.92917	0.92531	0.95378	0.97119
Specificity	0.53846	0.53846	0.5	0.53333	0.5
Precision	0.97436	0.9738	0.9738	0.97009	0.97925
FPR	0.46154	0.46154	0.5	0.46667	0.5
FNR	0.05	0.070833	0.074689	0.046218	0.028807
NPV	0.53846	0.53846	0.5	0.53333	0.5
FDR	0.025641	0.026201	0.026201	0.029915	0.020747
F1-Score	0.96203	0.95096	0.94894	0.96186	0.97521
MCC	0.40919	0.35233	0.30852	0.4365	0.43192