Research Article
Global Optimization Ensemble Model for Classification Methods
Table 12
Results of diabetes dataset: comparison of optimized classification accuracy using GMC model with simple classification using different classifiers.
| | Algorithm | Classification accuracy | Optimized classification accuracy | Improvement % |
| | K-NN | 73.70% | 77.48% | 4% | | Decision tree | 74.0% | 75.39% | 1.39% | | W-PART | 73.83% | 77.34% | 3.51% | | W-Prism | 57.42% | 67.97% | 10.55% | | W-J48 | 74.08% | 77.22% | 3.14% | | W-AODE | 66.54% | 69.14% | 2.6% | | Logistic regression | 76.00% | 77.95% | 1.95% |
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