Table 5.

Features selection test according to feature selection methods

Test number	Method	Selects	Search algorithms	Selected subsets/features (mean value among the three trials)
1	Principal components	Attributes	Ranker	Num-OC, Wcl, tetaSD-OC, Wop, Num-PS
2	SVM	Attributes	Ranker	fSD_PS, WcTF, tetaSD-PS, tetaSD-OC, Wps, WoTF, Num-PS
3	Consistency	Subset	Greedy SW	Num-OC, Wop, fSD-PS, tetaSD-PS
4	J48	Subset	Greedy SW	Num-OC, WcTF, Wop
5	Filtered subset evaluation	Subset	Genetic search	Num-PS, Num-OC, tetaSD-PS, fSD-PS, Wcl
6	Information gain	Attributes	Ranker	PwrP, fSD-TF, Num-OC, tetaSD-TF, Wsp, Wps, Num-PS
7	Gain ratio	Attributes	Ranker	PwrP, fSD-TF, Num-OC, tetaSD-TF, Wsp, Wps, Num-PS
8	Chi square attribute evaluation	Attributes	Ranker	PwrP, fSD-TF, tetaSD-TF, Num-OC, Wsp, Wps, Num-PS