Research Article
A Parallel Genetic Algorithm Based Feature Selection and Parameter Optimization for Support Vector Machine
Table 2
Comparisons between CGPGA-SVM and GA-SVM.
| Dataset | CGPGA-SVM | GA-SVM |
| Ionosphere | 98.85 ± 2.01 | 98.03 ± 2.64 | Breast cancer | 98.53 ± 1.16 | 98.39 ± 1.75 | Australia | 90.13 ± 2.39 | 87.10 ± 2.64 | Diabetes | 81.76 ± 3.37 | 79.04 ± 2.44 | Vehicle | 86.05 ± 3.54 | 83.69 ± 2.64 | Vowel | 99.29 ± 0.68 | 98.58 ± 1.44 | Car | 99.83 ± 0.39 | 99.36 ± 0.51 | Splice | 92.66 ± 1.43 | 89.07 ± 1.81 | DNA | 96.79 ± 1.31 | 95.83 ± 1.01 | WaveForm | 87.81 ± 1.60 | 82.60 ± 2.56 | Svmguide1 | 96.66 ± 0.76 | 96.69 ± 0.98 | Mushrooms | 100.0 ± 0.00 | 99.96 ± 0.06 |
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