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Effect of the SFS method on classification results
| Classifier | Used Features | ACC (after used SFS) |
ACC (before used SFS) |
|---|---|---|---|
| Polynomial-SVM | 19 | 0.9556 | 0.9556 |
| RBF-SVM | 18 | 0.9667 | 0.9611 |
| Linear-LDA | 11 | 0.8388 | 0.8111 |
| Quadratic-LDA | 15 | 0.9111 | 0.9056 |
| Euclidean-kNN | 19 | 0.9833 | 0.9833 |
| Chebychev-kNN | 13 | 0.9444 | 0.9056 |
| PLSR | 17 | 0.8277 | 0.8111 |
The highest value in each classifier is indicated in boldface
