Table 6.

Performance metrics of the proposed CNN-based models for the hybrid dataset.

Dataset	Model	Accuracy	Precision	Sensitivity	Specificity	F1-Score	FPR
	CNN	92.26 ± 0.94	89.54 ± 1.69	94.69 ± 0.74	90.11 ± 1.44	92.04 ± 1.02	9.89 ± 1.44
	CNN+SVM	94.24 ± 0.41	94.23 ± 0.42	94.25 ± 0.59	94.24 ± 0.4	94.24 ± 0.4	5.76 ± 0.4
Hybrid	CNN+LR	95.34 ±0.25	95.71 ± 0.34	95.01 ± 0.3	95.68 ± 0.33	95.36 ± 0.25	4.32 ± 0.33
Dataset	CNN+RF	94.93 ± 0.38	97.34 ± 0.43	92.87 ± 0.65	97.21 ± 0.44	95.05 ± 0.36	2.79 ± 0.44
	CNN+KNN	90.43 ± 0.96	98.24 ± 1.05	84.99 ± 1.37	97.94 ± 1.16	91.13 ± 0.84	2.06 ± 1.16
	CNN+DT	91.11 ± 0.42	90.56 ± 0.76	91.59 ± 0.86	90.67 ± 0.64	91.06 ± 0.41	9.33 ± 0.64