AutoML
Feature Selection
Introduced by Ghojogh et al. in Feature Selection and Feature Extraction in Pattern Analysis: A Literature ReviewFeature selection, also known as variable selection, attribute selection or variable subset selection, is the process of selecting a subset of relevant features (variables, predictors) for use in model construction.
Source: Feature Selection and Feature Extraction in Pattern Analysis: A Literature ReviewPapers
| Paper | Code | Results | Date | Stars |
|---|
Tasks
| Task | Papers | Share |
|---|---|---|
| Dimensionality Reduction | 31 | 5.65% |
| Classification | 30 | 5.46% |
| Feature Importance | 23 | 4.19% |
| Decision Making | 21 | 3.83% |
| Feature Engineering | 14 | 2.55% |
| Image Classification | 11 | 2.00% |
| Emotion Recognition | 10 | 1.82% |
| Clustering | 10 | 1.82% |
| Fairness | 10 | 1.82% |
Usage Over Time
Components
| Component | Type |
|
|---|---|---|
| 🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |
