Table 3.

Performance of the machine learning algorithms on test data for positive value.

Model	Accuracy	Precision	Sensitivity	F_Score	AUC
Logistic regression	75.4 (68.9, 89.4)	0.66 (54.1, 77.9)	84.38 (57.8, 92.9)	0.72 (60.7, 83.3)	0.87 (78.6, 95.4)
Decision tree	75.0 (65, 3, 84.7)	82.0 (73.4, 90.6)	69.0 (58.7, 79.4)	75.0 (65, 3, 84.7)	83.0 (69.9, 90.0)
Support vector machine	72.0 (60.7, 83.3)	63.0 (50.8, 70.1)	70.8 (59.4, 82.2)	67.0 (55.2, 78.8)	80.0 (69.9, 90.0)
Random forest	69.0 (58.7, 79.4)	62.0 (49.8, 74.1)	70.8 (59.4, 82.2)	61.0 (48.8, 73.2)	83.0 (69.9, 90.0)