A newer version of the Gradio SDK is available: 6.11.0
metadata
title: Customer Churn Survival Analysis
emoji: 🔍
colorFrom: yellow
colorTo: indigo
sdk: gradio
sdk_version: 4.44.0
app_file: app.py
pinned: false
short_description: Customer Churn Prediction and Explainability
python_version: '3.12'
🔍 Customer Churn Survival Analysis
Complete analysis of churn risk using XAI (SHAP) and Survival Analysis.
🎯 Features
- Explainable AI: It explains why a customer has been classified as churner or non-churner, given the information present in the dataset
- Survival Analysis: It predicts when a customer is likely to churn and how much risk there is
- Interactive Visualizations: Plots shown with Gradio
🚀 How to Use It
- Choose between "Random Customer" or "Specific Customer"
- Click on "Analyze Customer"
- Explore the results in 3 tabs:
- XAI: SHAP values
- Survival Analysis: Risk timeline and Survival Probability Distribution through time
- Details: Customer Feature Values
🛠️ Models
- XGBoost Classifier: Churn Prediction
- Cox Proportional Hazards: Survival analysis
- SHAP: Explainability
📊 Dataset
Bank Customer Churn dataset with 200 test customers.