TABLE 2.

Accuracy of the important multi-label classifiers with different features on training and test datasets.

Method	Feature	Number of Features	Accuracy
			Training dataset	Test dataset
RAKEL_RF	Embedding features	702	0.542	0.536
RAKEL_SVM	Embedding features	746	0.542	0.537
RAKEL_RF	Embedding features	48	0.530	0.530
RAKEL_RF	Domain features	26	0.429	0.426
RAKEL_SVM	Domain features	27	0.429	0.428
RAKEL_RF	Linkage features	233	0.462	0.460
RAKEL_SVM	Linkage features	234	0.432	0.424
RAKEL_RF	Domain and linkage features	221	0.470	0.462
RAKEL_SVM	Domain and linkage features	227	0.449	0.433