Air Pollution Classification & Model Comparison

This project classifies air pollution levels as High or Low using sensor data from China (2015-2025). It trains and compares three machine learning models: Support Vector Machine (SVM), Logistic Regression, and Decision Tree.

🚀 Live Demo

Click here to view the Streamlit App

📊 Models Used

• SVM (Support Vector Machine): Good for high-dimensional boundaries.
• Logistic Regression: A baseline linear classifier.
• Decision Tree: Provides interpretable decision rules.

🛠️ Tech Stack

• Python (Pandas, NumPy, Scikit-learn)
• Streamlit (Web Interface)
• Joblib (Model persistence)

📂 Project Structure

• app.py: Main Streamlit application.
• *.pkl: Trained model files.
• requirements.txt: Python dependencies.

🏃‍♂️ How to Run Locally

1. Clone the repository.
2. Install dependencies: pip install -r requirements.txt
3. Run the app: streamlit run app.py