|
|
|
|
|
--- |
|
|
library_name: autogluon |
|
|
pipeline_tag: tabular-classification |
|
|
license: mit |
|
|
tags: |
|
|
- automl |
|
|
- tabular |
|
|
- autogluon |
|
|
- sklearn |
|
|
model_name: Football Elite Classifier — AutoML (AutoGluon Tabular) |
|
|
language: |
|
|
- en |
|
|
--- |
|
|
|
|
|
|
|
|
# Football Elite Classifier — AutoML (AutoGluon Tabular) |
|
|
|
|
|
**Task:** Binary classification — predict `Elite` (0/1) from tabular receiver stats. |
|
|
|
|
|
## Dataset |
|
|
- **Source:** <classmate name + HF dataset link if public> |
|
|
- **Split:** Stratified Train/Test = 80/20 on the **original** split. |
|
|
- **Features:** ['Tgt', 'Rec', 'Yds', 'YBC_per_R', 'YAC_per_R', 'ADOT', 'Drop_pct', 'Rat'] |
|
|
- **Target:** `Elite` (0/1) |
|
|
- **Preprocessing:** Identifier columns dropped (e.g., Player). Numeric coercion; rows with NA removed. |
|
|
|
|
|
## Training (AutoML) |
|
|
- **Framework:** AutoGluon Tabular |
|
|
- **Preset:** `best_quality` |
|
|
- **Time budget:** 300s |
|
|
- **Seed:** 42 |
|
|
- **Eval metric:** F1 (binary) |
|
|
- **Notes:** AutoGluon performs model selection, ensembling, and stacking automatically. |
|
|
|
|
|
## Results (Held-out Test) |
|
|
```json |
|
|
{ |
|
|
"accuracy": 0.8333333333333334, |
|
|
"f1": 0.8 |
|
|
} |
|
|
|
|
|
|
|
|
## Limitations & Ethics |
|
|
- Correlations do not imply causation; labels may reflect selection bias. |
|
|
- Out-of-distribution players/contexts may reduce performance. |
|
|
- Intended for coursework, not for real personnel decisions. |
|
|
|
|
|
## License |
|
|
- Code & weights: <MIT/Apache-2.0 or course-required license> |
|
|
|
|
|
## Acknowledgments |
|
|
AutoML with [AutoGluon Tabular]. |
|
|
Trained in Google Colab. |
|
|
GenAI tools assisted with boilerplate and doc structure. |
|
|
James Kramers hugging face dataset |
|
|
|
