Feature Selection on JA with random extraneous features (Precision/Recall)
98.1PrecisionXGBoost
Evaluation results
| Method | Links | ||
|---|---|---|---|
| XGBoost% extraneous features=502023.11 | 98.1 | 98.1 | |
| AM% extraneous features=502023.11 | 67.6 | 67.6 | |
| AGL% extraneous features=502023.11 | 66.5 | 66.5 | |
| Lasso% extraneous features=502023.11 | 66.1 | 66.1 | |
| RF% extraneous features=502023.11 | 66.1 | 66.1 | |
| Univariate% extraneous features=502023.11 | 64.8 | 64.8 | |
| 1L Lasso% extraneous features=502023.11 | 64.4 | 64.4 | |
| LassoNet% extraneous features=502023.11 | 64.4 | 64.4 | |
| Deep Lasso% extraneous features=502023.11 | 64.1 | 64.1 | |
| Lasso% extraneous features=752023.11 | 62.2 | 62.2 | |
| Deep Lasso% extraneous features=752023.11 | 57.6 | 57.6 | |
| XGBoost% extraneous features=752023.11 | 56.7 | 56.7 | |
| RF% extraneous features=752023.11 | 55.9 | 55.9 | |
| AGL% extraneous features=752023.11 | 54.1 | 54.1 | |
| Univariate% extraneous features=752023.11 | 53.7 | 53.7 | |
| 1L Lasso% extraneous features=752023.11 | 53.1 | 53.1 | |
| LassoNet% extraneous features=752023.11 | 41.5 | 41.5 |