Table 5.

Performance evaluation metrics of eight classifiers for original dataset consisting of PL+ and PL- molecules based on percentage split of 66:34.

Classifiers	Sensitivity	Specificity	Accuracy	AUC	MCC
Navie Bayes	70.3	84.4	76.8	0.831	0.548
SMO	70.3	87.5	78.3	0.789	0.581
IBK	75.7	84.4	79.7	0.789	0.599
RARF	78.4	81.3	79.7	0.893	0.595
PART	56.8	81.3	68.1	0.700	0.388
JRip	78.4	65.6	72.5	0.733	0.445
RandomForest	75.7	81.3	78.3	0.868	0.568
J48	70.3	71.9	71.0	0.735	0.420