Customer Churn Prediction

A machine learning project to predict customer churn using synthetic data and various ML models.

Features

• Logistic Regression, Random Forest, SVM, and Gradient Boosting models.
• Synthetic dataset generated with customer information.
• Preprocessing pipeline with feature engineering.
• Model evaluation with accuracy and classification reports.

Project Structure

CustomerChurnPrediction/ ├── churn_prediction.py # Main script for ML pipeline ├── data/ │ └── churn_data.csv # Dataset (generated) ├── README.md # Project documentation ├── requirements.txt # Dependencies

Installation

1. Clone the repository:

   git clone <repo-url>
   cd CustomerChurnPrediction
   

Install dependencies:

pip install -r requirements.txt

Run the script:

python churn_prediction.py

The results, including accuracy and classification reports, are saved in results.txt.