https://github.com/ghufranbarcha/linear-regression-training-app

This project is a Streamlit application that allows users to upload a CSV file, select variables, and train a linear regression model. The app provides an easy-to-use interface for selecting dependent and independent variables, scaling data, applying polynomial regression, and evaluating model performance.
https://github.com/ghufranbarcha/linear-regression-training-app

data-science machine-learning python scikit-learn streamlit

Last synced: 16 days ago
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This project is a Streamlit application that allows users to upload a CSV file, select variables, and train a linear regression model. The app provides an easy-to-use interface for selecting dependent and independent variables, scaling data, applying polynomial regression, and evaluating model performance.

• Host: GitHub
• URL: https://github.com/ghufranbarcha/linear-regression-training-app
• Owner: GhufranBarcha
• Created: 2024-07-17T15:29:17.000Z (7 months ago)
• Default Branch: main
• Last Pushed: 2024-08-17T12:41:38.000Z (6 months ago)
• Last Synced: 2024-12-02T23:08:46.500Z (2 months ago)
• Topics: data-science, machine-learning, python, scikit-learn, streamlit
• Language: Python
• Homepage: https://linear-regression-training-app.streamlit.app/
• Size: 4.88 KB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Linear Regression Model Training App

This project is a **Streamlit** application that allows users to upload a CSV file, select variables, and train a linear regression model. The app provides an easy-to-use interface for selecting dependent and independent variables, scaling data, applying polynomial regression, and evaluating model performance.

Check the project: https://linear-regression-training-app.streamlit.app/

## Features

- **CSV File Upload**: Upload your dataset directly through the app.

- **Variable Selection**: Choose the dependent and independent variables for model training.

- **Data Scaling**: Automatically scales the independent variables.

- **Polynomial Regression**: Option to apply polynomial regression with a selectable degree.

- **Model Training**: Trains a linear regression model and provides predictions.

- **Performance Metrics**: Displays R², MAE, RMSE, and MSE for evaluating the model.

- **Variable Impact**: Displays the impact of each independent variable on the model.

## Project Structure

- `app.py`: Main script for running the Streamlit application.

## How to Run

1. **Clone the Repository**:

   ```bash

   git clone https://github.com/GhufranBarcha/linear-regression-app.git

   cd linear-regression-app