Table 2 Performance comparison of different classifier.

Classifier	Attributes	SN	SP	Mcc	Accuracy (%)	ROC Area
Random forest	13440	0.831	0.687	0.523	75.878	0.850
LibD3C	13440	0.820	0.700	0.524	76.0045	0.846
J48	13440	0.688	0.683	0.371	68.5491	0.678
Bayes Network	13440	0.810	0.597	0.417	70.3646	0.761
Naive Bayes	13440	0.882	0.264	0.185	57.2768	0.690
KNN-IB1	13440	0.639	0.765	0.408	70.2158	0.706
AdaBoostM1	13440	0.782	0.605	0.393	69.3601	0.763
Bagging	13440	0.786	0.696	0.483	74.0699	0.822
GBDT	13440	0.718	0.705	0.456	72.7902	0.818
Random tree	13440	0.673	0.672	0.346	67.2842	0.673
RandomSubSpace	13440	0.819	0.662	0.486	74.0179	0.826
SMO	13440	0.677	0.749	0.427	71.2798	0.713
LibSVM	13440	0.947	0.307	0.331	62.7232	0.627

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