MPG Data Analysis and Prediction

This project is a Streamlit web app that predicts whether a car’s mileage (MPG) is above or below average using the Auto MPG dataset and logistic regression.

Features

• Data preprocessing and model training
• Model performance metrics and confusion matrix visualization
• Interactive user input for car features
• Instant prediction of mileage impact

How to Run

1. Install requirements:

   pip install streamlit scikit-learn pandas numpy seaborn matplotlib
   

2. Start the app:

   streamlit run MPG_DATA_1.py
   

Usage

• Enter car features in the sidebar and click Predict to see if the car has positive or negative mileage impact.

File

• MPG_DATA_1.py: Main Streamlit app
• auto-mpg.csv: Dataset (required in the same directory)