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 | 30 | 4.43% |
| Feature Importance | 25 | 3.69% |
| Computational Efficiency | 23 | 3.40% |
| regression | 22 | 3.25% |
| Decision Making | 21 | 3.10% |
| Prediction | 21 | 3.10% |
| Classification | 20 | 2.95% |
| Feature Engineering | 13 | 1.92% |
| Recommendation Systems | 13 | 1.92% |
Usage Over Time
Components
| Component | Type |
|
|---|---|---|
| 🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |
