Research Article
Global Optimization Ensemble Model for Classification Methods
Table 10
Results of sonar dataset: comparison of optimized classification accuracy using GMC model with simple classification using different classifiers.
| | Algorithm | Classification accuracy | Optimized classification accuracy | Improvement % |
| | K-NN | 69.71% | 74.57% | 4.86% | | Decision Tree | 73.57% | 83.67% | 10.1% | | W-PART | 75.48% | 83.17% | 7.69% | | W-Prism | 48.02% | 63.38% | 15.36% | | W-J48 | 70.24% | 82.21% | 11.97% | | Rule induction | 71.66% | 76.48% | 4.82% | | Random forest | 68.26% | 75.36% | 7.1% | | Logistic regression | 74.55% | 80.29% | 5.74% |
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