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superkart-sales-xgb-model
vinayakdnrdd/superkart-sales-xgb-model
superkart-sales-xgb-model is a tabular regression model from vinayakdnrdd. Use it for the tabular regression task on the model card, and read the license before you ship it in a product. It is set up for scikit-learn.
This repository contains a serialized scikit-learn Pipeline (preprocessing + XGBoost regressor) trained on the SuperKart dataset.
Access
Public
Updated Jan 10, 2026
Repo size
3.2 MB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.joblib3.2 MB · 100%
At a glance
- Task
- Tabular Regression
- Library
- scikit-learn
- Access
- Public
- Created
- Jan 10, 2026
- Updated
- Jan 10, 2026
- SHA
- 5396f660
Model card
From the Hugging Face model README
SuperKart Sales Forecast Model (XGBoost Regressor)
This repository contains a serialized scikit-learn Pipeline (preprocessing + XGBoost regressor) trained on the SuperKart dataset.
Target
Product_Store_Sales_Total
Training data
- Dataset repo:
vinayakdnrdd/superkart-sales-data processed/train.csvprocessed/test.csv
Evaluation (test split)
- RMSE: 231.3869
- MAE: 73.3437
- R²: 0.9531
Best Hyperparameters
{
"model__subsample": 0.85,
"model__reg_lambda": 1.0,
"model__n_estimators": 800,
"model__max_depth": 6,
"model__learning_rate": 0.03,
"model__colsample_bytree": 0.85
}
How to use
import joblib
from huggingface_hub import hf_hub_download
model_path = hf_hub_download('vinayakdnrdd/superkart-sales-xgb-model', filename='superkart_sales_model.joblib')
model = joblib.load(model_path)
y_pred = model.predict(X) # X: pandas DataFrame with training feature columns
- Task
- Tabular Regression
- Library
- scikit-learn
- Languages
- en
- Created
- Jan 10, 2026
- Updated
- Jan 10, 2026