Table 3.

Comparison of GTB with other typical classifiers on primary ontology features

Method	Precision	Recall	F-Measure	MCC	AUC
GTB	0.526	0.53	0.523	0.052	0.528
kNN	0.514	0.514	0.513	0.028	0.516
SVM	0.509	0.491	0.478	-0.019	0.491
Logistic	0.506	0.506	0.506	0.012	0.504
Naive Bayes	0.479	0.479	0.478	-0.043	0.46
Random forest	0.499	0.499	0.478	-0.002	0.499
AdaBoost	0.501	0.501	0.425	0.002	0.497
LogitBoost	0.499	0.499	0.479	-0.002	0.495

The boldface figures indicate that GTB achieves the best performance compared with other 7 typical classifiers trained on primary ontology features