Table 3:
Comparisons between CGPGA-SVM and grid search.
Dataset
CGPGA-SVM
Grid search
p
values
Tenfold cross validation accuracy (%)
Number of selected features
Tenfold cross validation accuracy (%)
Number of selected features
Ionosphere
98.85 ± 2.01
13.8 ± 3.46
93.16 ± 3.00
34.0 ± 0.00
0.005
Breast cancer
98.53 ± 1.16
2.60 ± 0.84
96.77 ± 1.81
10.0 ± 0.00
0.039
Australia
90.13 ± 2.39
5.10 ± 1.60
85.51 ± 4.46
14.0 ± 0.00
0.011
Diabetes
81.76 ± 3.37
3.90 ± 0.99
76.44 ± 3.74
8.00 ± 0.00
0.014
Vehicle
86.05 ± 3.54
10.3 ± 1.34
78.60 ± 3.29
18.0 ± 0.00
0.005
Vowel
99.29 ± 0.68
6.70 ± 0.48
98.88 ± 1.00
13.0 ± 0.00
0.037
Car
99.83 ± 0.39
6.00 ± 0.00
99.48 ± 0.51
6.00 ± 0.00
0.046
Splice
92.66 ± 1.43
26.7 ± 3.53
92.03 ± 1.52
60.0 ± 0.00
0.386
DNA
96.79 ± 1.31
87.1 ± 4.53
96.05 ± 1.09
180. ± 0.00
0.005
WaveForm
87.81 ± 1.60
21.1 ± 2.69
86.68 ± 1.47
40.0 ± 0.00
0.037
Svmguide1
96.66 ± 0.76
2.40 ± 0.52
96.32 ± 0.71
4.00 ± 0.00
0.594
Mushrooms
100.0 ± 0.00
42.5 ± 3.54
99.98 ± 0.04
112. ± 0.00
0.317
indicates significance at 0.005 level.