Research Article
Toward a General-Purpose Heterogeneous Ensemble for Pattern Classification
Table 6
Performance on the different data mining datasets.
| ā | Datasets (AUC) | Av | RA | BR | HE | PI | SP | SO | IO | LI | HA | VO | AU | TR |
| SVM | 0.9941 | 0.8809 | 0.824 | 0.9708 | 0.9517 | 0.9814 | 0.7558 | 0.7012 | 0.9855 | 0.9164 | 0.714 | 0.8796 | 7.3077 | RS-SVM | 0.9931 | 0.9076 | 0.8221 | 0.9771 | 0.9591 | 0.9795 | 0.7411 | 0.6399 | 0.9853 | 0.9221 | 0.6931 | 0.8745 | 8.6923 | GPC | 0.9924 | 0.9024 | 0.827 | 0.979 | 0.9409 | 0.9713 | 0.729 | 0.6804 | 0.9882 | 0.9267 | 0.7295 | 0.8788 | 8.000 | RS_AB | 0.991 | 0.9101 | 0.8229 | 0.988 | 0.9371 | 0.9788 | 0.7581 | 0.6727 | 0.9887 | 0.9313 | 0.735 | 0.8831 | 7.000 | RS_RB | 0.9925 | 0.9169 | 0.8208 | 0.9873 | 0.9334 | 0.9851 | 0.7664 | 0.6071 | 0.9884 | 0.9326 | 0.674 | 0.8731 | 7.3846 | DL1 | 0.9943 | 0.8852 | 0.8252 | 0.966 | 0.8794 | 0.9222 | 0.7541 | 0.6751 | 0.9795 | 0.9155 | 0.7338 | 0.8664 | 8.7692 | DL2 | 0.9941 | 0.8754 | 0.8149 | 0.9691 | 0.8789 | 0.9242 | 0.7478 | 0.6679 | 0.9808 | 0.9088 | 0.7318 | 0.8631 | 10.3077 | DL3 | 0.9943 | 0.8941 | 0.8193 | 0.9684 | 0.8501 | 0.9022 | 0.6966 | 0.6537 | 0.9787 | 0.9154 | 0.7351 | 0.8553 | 10.2308 | S_D | 0.9942 | 0.883 | 0.8238 | 0.9683 | 0.8781 | 0.9297 | 0.751 | 0.6772 | 0.9813 | 0.9186 | 0.7357 | 0.8674 | 8.6154 | E1 | 0.992 | 0.9096 | 0.8277 | 0.9856 | 0.9426 | 0.9772 | 0.7532 | 0.6868 | 0.9896 | 0.9331 | 0.7372 | 0.885 | 6.000 | E2 | 0.9924 | 0.9124 | 0.8285 | 0.988 | 0.9426 | 0.9817 | 0.7727 | 0.6724 | 0.9897 | 0.935 | 0.7257 | 0.8856 | 5.3846 | E3 | 0.9933 | 0.9141 | 0.8288 | 0.9873 | 0.9508 | 0.9819 | 0.7723 | 0.6726 | 0.989 | 0.9343 | 0.7258 | 0.8864 | 5.0769 | E4 | 0.9934 | 0.9113 | 0.8294 | 0.9862 | 0.942 | 0.9805 | 0.7717 | 0.6794 | 0.9895 | 0.9339 | 0.7297 | 0.8861 | 5.2308 |
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