Table 10.

Comparison of classification performance achieved by different synergy between feature selection methods and classification models.

Feature Selection (FS)	Performance Metrics	Classifiers
		SVM	ANN	NB	KNN	LR	LDA	DT	Proposed ECBDT
All features (No FS)	Sensitivity	72.18%	75.19%	66.17%	72.93%	71.43%	75.19%	71.43%	74.48%
	Specificity	95.47%	94.48%	93.41%	95.51%	94.82%	95.12%	94.10%	96.11%
	F-score	57.31%	55.25%	46.93%	57.91%	54.44%	57.64%	51.91%	61.73%
	Accuracy	94.21%	93.44%	91.95%	94.29%	93.57%	94.05%	92.88%	94.98%
PSO-ANN	Sensitivity	73.65%	70.91%	69.16%	74.29%	69.23%	69.16%	71.83%	76.47%
	Specificity	96.64%	96.11%	95.67%	96.72%	96.11%	95.67%	96.32%	97.09%
	F-score	76.29%	77.33%	74.30%	75.96%	69.96%	74.30%	80.42%	80.28%
	Accuracy	97.21%	97.25%	96.64%	97.21%	97.29%	96.64%	97.73%	97.73%
GA-ANN	Sensitivity	87.97%	86.47%	64.66%	87.97%	87.22%	64.66%	86.47%	86.47%
	Specificity	97.22%	97.09%	99.44%	98.20%	97.31%	99.44%	98.63%	98.93%
	F-score	74.29%	72.78%	74.14%	80.14%	74.36%	74.14%	82.14%	84.25%
	Accuracy	96.72%	96.52%	97.57%	97.65%	96.76%	97.57%	97.98%	98.26%
SA	Sensitivity	85.71%	86.47%	90.23%	84.21%	84.96%	90.23%	84.21%	87.22%
	Specificity	97.22%	97.73%	97.60%	97.52%	98.37%	97.60%	99.14%	99.27%
	F-score	73.08%	76.41%	77.67%	73.93%	79.58%	77.67%	84.53%	87.22%
	Accuracy	96.60%	97.13%	97.21%	96.80%	97.65%	97.21%	98.34%	98.62%
Proposed SA-ANN	Sensitivity	85.71%	72.93%	72.93%	84.21%	79.70%	72.93%	86.47%	87.97%
	Specificity	97.22%	99.70%	99.66%	97.52%	98.16%	99.66%	99.27%	99.40%
	F-score	73.08%	81.86%	81.51%	73.93%	75.18%	81.51%	86.79%	87.79%
	Accuracy	96.60%	98.26%	98.22%	96.80%	97.17%	98.22%	98.58%	98.70%