Table 20.
Performance comparison of our method vs. mRMR for the imbalanced E. coli data set when identical numbers of features are selected.
AUC | Precision | Recall | F1 | MCC | ||||||
---|---|---|---|---|---|---|---|---|---|---|
N4 | 0.691 | 0.651 | 0.725 | 0.678 | 0.280 | 0.269 | 0.404 | 0.385 | 0.391 | 0.363 |
N5 | 0.690 | 0.675 | 0.737 | 0.687 | 0.295 | 0.254 | 0.421 | 0.371 | 0.407 | 0.356 |
N6 | 0.701 | 0.681 | 0.742 | 0.708 | 0.287 | 0.220 | 0.414 | 0.336 | 0.403 | 0.338 |
N7 | 0.714 | 0.686 | 0.735 | 0.712 | 0.275 | 0.212 | 0.400 | 0.326 | 0.392 | 0.333 |
N8 | 0.705 | 0.692 | 0.742 | 0.713 | 0.288 | 0.209 | 0.415 | 0.323 | 0.405 | 0.330 |
N9 | 0.707 | 0.692 | 0.726 | 0.713 | 0.293 > | 0.199 | 0.417 > | 0.312 | 0.401 | 0.322 |
N10 | 0.711 | 0.697 | 0.724 | 0.703 | 0.294 > | 0.193 | 0.418 > | 0.302 | 0.401 | 0.313 |
N11 | 0.714 < | 0.702 | 0.732 | 0.697 | 0.278 > | 0.187 | 0.403 | 0.295 | 0.393 | 0.306 |
N12 | 0.712 < | 0.704 | 0.725 | 0.683 | 0.292 | 0.192 | 0.416 | 0.300 | 0.400 | 0.305 |
N13 | 0.714 < | 0.715 | 0.733 | 0.713 | 0.287 | 0.250 | 0.413 | 0.370 | 0.400 | 0.360 |