FeatureSelect: a software for feature selection based on machine learning approaches

BMC Bioinformatics

Table 5 Essential statistical measurements for all classification datasets

DS	AL_NAME	SEN	PRE	FPR	ACC	DS	AL_NAME	SEN	PRE	FPR	ACC
CARCINOM(80%,N)	WCC	0.68	0.60	0.02	0.76	USPS(80%,O)	WCC	0.82	0.86	0.02	0.85
	LCA	0.68	0.60	0.02	0.76		LCA	0.82	0.83	0.02	0.85
	GA	0.68	0.60	0.02	0.75		GA	0.83	0.86	0.02	0.85
	PSO	0.68	0.60	0.02	0.76		PSO	0.87	0.88	0.02	0.87
	ACO	0.68	0.60	0.02	0.75		ACO	0.85	0.85	0.02	0.85
	ICA	0.68	0.60	0.02	0.76		ICA	0.81	0.89	0.02	0.86
	LA	0.68	0.60	0.02	0.75		LA	0.89	0.89	0.01	0.89
	HTS	0.68	0.60	0.02	0.58		HTS	0.79	0.82	0.03	0.81
	FOA	0.68	0.60	0.02	0.77		FOA	0.81	0.84	0.02	0.83
	DSOS	0.68	0.60	0.02	0.76		DSOS	0.80	0.80	0.02	0.82
	CUK	0.68	0.60	0.02	0.76		CUK	0.82	0.84	0.02	0.84
BASEHOCK(80%,F)	WCC	0.66	0.89	0.33	0.72	DRIVE(80%,N)	WCC	0.56	0.81	0.24	0.92
	LCA	0.70	0.83	0.30	0.75		LCA	0.56	0.81	0.24	0.92
	GA	0.57	0.72	0.43	0.49		GA	0.56	0.81	0.24	0.92
	PSO	0.58	0.71	0.42	0.50		PSO	0.52	0.80	0.25	0.91
	ACO	0.56	0.72	0.44	0.48		ACO	0.52	0.80	0.25	0.91
	ICA	0.58	0.72	0.42	0.51		ICA	0.56	0.81	0.24	0.92
	LA	0.68	0.67	0.32	0.68		LA	0.52	0.80	0.25	0.91
	HTS	0.53	0.71	0.47	0.44		HTS	0.33	0.63	0.33	0.89
	FOA	0.58	0.75	0.42	0.66		FOA	0.52	0.80	0.25	0.91
	DSOS	0.54	0.72	0.46	0.46		DSOS	0.52	0.80	0.25	0.91
	CUK	0.66	0.66	0.34	0.66		CUK	0.56	0.81	0.24	0.92

ISSN: 1471-2105