---
tags:
- sklearn
- regression
- sales-forecast
- RandomForest
library_name: sklearn
metrics:
- rmse
- r2
model-index:
- name: RandomForest
  results:
  - task:
      type: tabular-regression
      name: Sales Forecasting
    dataset:
      name: SuperKart Data
      type: tabular
    metrics:
      - type: rmse
        value: 280.8543593979435
      - type: r2
        value: 0.9308695977150697
---
# SuperKart Sales Prediction Model

## Model Description
This is a **RandomForest** model trained to predict sales revenue (`Product_Store_Sales_Total`) for SuperKart stores.
It utilizes a Scikit-Learn Pipeline that handles:
1. **Preprocessing**: OneHotEncoding for categorical variables and Scaling for numerical variables.
2. **Modeling**: The best performing regressor selected from Random Forest, Gradient Boosting, and XGBoost.

## Performance
- **RMSE**: 280.8544
- **R2 Score**: 0.9309
- **MAE**: 114.7186

## Usage
This model expects a pandas DataFrame with the same columns as the training set (Product_Weight, Product_Sugar_Content, etc.).