A logistic regression-based model 📈 predicting vehicle pass/fail for smog emissions checks 🏎️ 💨. Analyzes weight, horsepower, & displacement for eco-friendly 🌿 driving assessment.
The project focuses on building a model that categorizes vehicles based on their potential to pass or fail smog emissions tests. Utilizing logistic regression with gradient descent, this classifier aims to aid in eco-friendly driving assessments by predicting a vehicle's emission performance.
- Data Exploration: 📊 Analyze vintage car data, understand trends, and preprocess information for modeling.
- Logistic Regression: 📈 Utilizes a gradient descent algorithm for classification.
- Evaluation: 🧪 Assess model accuracy, tune parameters, and validate results.
- Visualization: 📉 Display visual insights and regression analysis results as graphs. Graphs will be generated in
pngformat inside thedata/directory.
- Installation: 💻 Clone the repository and install dependencies using
npm install. - Run:
▶️ Execute the project usingnpm start.
Contributions are welcome! Fork the repository, create a new branch, and submit a pull request with your enhancements or fixes.
This project is licensed under the GPL-3.0 License.
- Special thanks to the amazing communities of Node.js & TensorFlow JS.
Feel free to reach out at [email protected] for any queries.