Table 3.

Overall Performance analysis for the proposed brain tumour diagnosis model over diverse classifies

Measures	DT [37]	SVM [38]	NN [39]	DNN [34]	CNN [31]	Autoencoder [33]	ACV-DHOA-CNN-EC
“Accuracy”	0.94071	0.95257	0.94862	0.94466	0.94071	0.94071	0.96443
“Sensitivity”	0.96281	0.97908	0.96708	0.97095	0.95885	0.9668	0.98354
“Specificity”	0.45455	0.5	0.5	0.41667	0.5	0.41667	0.5
“Precision”	0.9749	0.97095	0.97917	0.97095	0.97899	0.97083	0.97951
“FPR”	0.54545	0.5	0.5	0.58333	0.5	0.58333	0.5
“FNR”	0.03719	0.020921	0.032922	0.029046	0.041152	0.033195	0.016461
“NPV”	0.45455	0.5	0.5	0.41667	0.5	0.41667	0.5
“FDR”	0.025105	0.029046	0.020833	0.029046	0.021008	0.029167	0.020492
“F1-Score”	0.96881	0.975	0.97308	0.97095	0.96881	0.96881	0.98152
“MCC”	0.37226	0.51531	0.41221	0.38762	0.37856	0.36919	0.50865