superkart-sales-predictor

SuperKart Sales Prediction Model

This is a RandomForestRegressor model trained to predict Product_Store_Sales_Total for the SuperKart dataset.

Training Data

The model was trained on data loaded from MonicaPopuri/superkart-dataset-train.

Model Architecture

• Algorithm: RandomForestRegressor
• Best Hyperparameters: {'model__max_depth': 20, 'model__min_samples_leaf': 5, 'model__n_estimators': 100}

Performance

• Mean Squared Error (MSE) on test set: 50229.91
• R-squared (R2) on test set: 0.96

Usage (Example)

import joblib
from huggingface_hub import hf_hub_download

model_path = hf_hub_download(repo_id="MonicaPopuri/superkart-sales-predictor", filename="superkart_sales_rf_model.joblib", repo_type='model')
model = joblib.load(model_path)

# Assuming 'new_data' is a pandas DataFrame with the same features as training data
# predictions = model.predict(new_data)