An Interior Point Method for 𝐿_1/2-SVM and Application to Feature Selection in Classification

Table 4

Feature selection performance comparison on UCI data sets (Cardinality).

No.	UCI Data Set	𝑛	𝑚	𝐿2-SVM		𝐿1-SVM		𝐿0-SVM		𝐿1/2-SVM
				Mean	Std	Mean	Std	Mean	Std	Mean	Std
1	Pima diabetes	768	8	8.00	0.00	7.40	0.89	6.20	1.10	7.60	1.52
2	Breast Cancer	683	9	9.00	0.00	8.60	1.22	6.40	2.07	8.40	1.67
3	Wine (3)	178	13	13.00	0.00	9.73	0.69	3.73	0.28	4.07	0.49
4	Image (7)	2100	19	19.00	0.00	8.20	0.53	3.66	0.97	5.11	0.62
5	SPECT	267	22	22.00	0.00	17.40	5.27	9.80	4.27	9	1.17
6	WDBC	569	30	30.00	0.00	9.80	1.52	9.00	3.03	5.60	2.05
7	Ionosphere	351	34	33.20	0.45	25.00	3.35	24.60	10.21	21.80	8.44
8	SPECTF	267	44	44.00	0.00	38.80	10.98	24.00	11.32	25.60	7.75
9	Sonar	208	60	60.00	0.00	31.40	13.05	27.00	7.18	13.60	10.06
10	Musk1	476	166	166.00	0.00	85.80	18.85	48.60	4.28	41	14.16
	Average cardinality		40.50	40.42		24.21		16.30		14.18