Semisupervised SVM Based on Cuckoo Search Algorithm and Its Application

Table 2

Comparison of numerical testing results.

Function	Algorithm	Maximum	Minimum	Average	Variance
	CS	0.0296	3.6427e-21	8.4440e-04	1.3215e-05
	CCCS	0.0218	7.8064e-33	8.1488e-04	1.2582e-05
	PSO	0.4786	0.0100	0.0158	0.0017
	CGSA	0.5362	0.0098	0.0108	3.0341e-04
	CS	0.6626	0	0.0029	0.0010
	CCCS	0.5690	0	0.0027	7.3280e-04
	PSO	26.6960	10.6037	10.6359	0.5174
	CGSA	2.2731	9.4231e-10	0.0431	0.0358
	CS	0.7740	1.8489e-32	0.0031	0.0013
	CCCS	0.6371	0	0.0031	0.0011
	PSO	5.3003e+03	0.0101	17.4638	5.8025e+04
	CGSA	1.3660e+04	3.0835e-18	30.6816	2.8436e+05
	CS	0.6047	0	0.0034	0.0012
	CCCS	0.5616	0	0.0022	6.2698e-04
	PSO	3.3220e+05	0.0100	951.0100	2.7004e+08
	CGSA	14.8439	9	9.0251	0.1110
	CS	1.1919	2.0256e-31	0.0044	0.0028
	CCCS	0.9859	0	0.0036	0.0019
	PSO	20.2544	3.7769	4.9084	6.4985
	CGSA	20.7509	3.4519e-09	0.2963	1.6965
	CS	1.1351	0	0.0048	0.0031
	CCCS	1.0239	0	0.0038	0.0022
	PSO	5.4272e+03	1.5607	24.8489	7.5573e+04
	CGSA	44.0831	3.6602	4.2440	7.2125
	CS	0.5721	1.1381e-30	0.0032	0.0011
	CCCS	0.5493	0	0.0027	7.9073e-04
	PSO	4.9874e+04	0.0298	143.0958	5.5309e+06
	CGSA	268.3960	60.6185	60.9033	45.2938
	CS	0.1298	4.4998e-30	0.0021	1.5972e-04
	CCCS	0.0984	0	0.0014	7.1452e-05
	PSO	2.2087	0.0050	0.0174	0.0128
	CGSA	129.8682	6.4933	7.9713	90.9936