Table 3 Accuracy, Sensitivity, and Specificity of classifiers for several feature selection and non-feature selection processes.

Classifier	Chi-square features			Two-way ANOVA test features			Regression analysis features
Classifier	Classification Accuracy	Sensitivity	Specificity	Classification Accuracy	Sensitivity	Specificity	Classification Accuracy	Sensitivity	Specificity
Decision tree	0.75	0.84	0.40	0.73	0.89	0.47	0.78	0.87	0.53
Random forest	1.0	1.0	1.0	0.992	1.0	1.0	0.83	0.95	0.73
Multinomial Naïve Bayes	0.47	0.96	0.60	0.73	0.92	0.46	0.72	0.97	0.60
Gaussian Naïve Bayes	0.70	0.96	0.40	0.72	1.0	0.0	0.78	0.97	0.60

	Chi-square ∪ two-way ANOVA ∪ regression			Chi-square ∩ Two-way ANOVA ∩ regression			Without feature selection
Decision tree	0.75	0.81	0.48	0.80	0.95	0.68	0.77	0.92	0.55
Random forest	1.0	1.0	1.0	0.78	0.89	0.62	0.75	0.98	0.75
Multinomial Naïve Bayes	0.59	0.87	0.36	0.66	0.93	0.50	0.93	1.0	1.0
Gaussian Naïve Bayes	0.60	0.87	0.33	0.66	0.93	0.50	1.0	1.0	1.0

Quick links

Search