Research Article
Hybrid Feature Selection Based Weighted Least Squares Twin Support Vector Machine Approach for Diagnosing Breast Cancer, Hepatitis, and Diabetes
Table 6
Comparison of predictive accuracies of proposed and other classifiers for Hepatitis.
| Reference | Approach | Predictive accuracy |
| This study | HFS + WLSTSVM | 87.50% |
Ster and Dobnikar [27] | CART decision tree | 82.7% | Ster and Dobnikar [27] | LVQ | 83.2% | Ster and Dobnikar [27] | MLP with BP | 82.1% | Ster and Dobnikar [27] | ASR | 85% | Ster and Dobnikar [27] | QDA | 85.8% |
Rafal Adamczak [47] | RBF (Tooldiag) | 79.0% | Rafal Adamczak [47] | MLP + BP (Tooldiag) | 77.4% |
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