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tags:
- regression
- sales-forecasting
- sklearn
metrics:
- rmse
- mae
- r2
---
# SuperKart Sales Forecast Model
**Algorithm:** Random Forest
**Task:** Regression — predict `Product_Store_Sales_Total`
## Performance (held-out test set)
| Metric | Value |
|--------|-------|
| RMSE | 279.80 |
| MAE | 113.79 |
| R² | 0.9314 |
| MAPE | 4.06 % |
## Best Hyperparameters
```json
{
"model__max_depth": 10, "model__min_samples_split": 5, "model__n_estimators": 300 } ```
## Usage
```python
import joblib
from huggingface_hub import hf_hub_download
path = hf_hub_download(repo_id="vikashHugFace/superkart-sales-forecast-model", filename="best_model.pkl")
model = joblib.load(path)
predictions = model.predict(X_new)
```
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