https://github.com/developerwilliams/customer-churn-prediction

This code trains a basic Random Forest model for churn prediction.
https://github.com/developerwilliams/customer-churn-prediction

Last synced: 4 months ago
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This code trains a basic Random Forest model for churn prediction.

• Host: GitHub
• URL: https://github.com/developerwilliams/customer-churn-prediction
• Owner: DeveloperWilliams
• License: mit
• Created: 2024-10-29T17:48:23.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2024-10-29T18:10:54.000Z (about 1 year ago)
• Last Synced: 2025-04-03T23:06:07.211Z (10 months ago)
• Language: Python
• Size: 3.91 KB
• Stars: 3
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: readme.md
  • License: LICENSE

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README

          
# Customer Churn Prediction

## Overview

This project builds a machine learning model to predict customer churn based on historical data. It includes data preprocessing, model training, and performance evaluation.

## Features

- **Data Preprocessing**: Encodes categorical data and scales features.

- **Modeling**: Trains a Random Forest and Logistic Regression model.

- **Evaluation**: Evaluates models using accuracy, precision, recall, and AUC.

## Installation

1. Install dependencies: `pip install -r requirements.txt`

2. Run `python train.py --data customer_data.csv --output model.pkl` 

## Technologies Used

- `scikit-learn` for machine learning

- `pandas` and `numpy` for data handling

- `matplotlib` for visualization