🏦 Credit Risk Prediction System
Sistem prediksi risiko kredit menggunakan ensemble machine learning models.
🚀 Features
- Ensemble Model: Kombinasi dari XGBoost, LightGBM, CatBoost, dan LSTM
- Real-time Prediction: Prediksi risiko kredit secara real-time
- User-friendly Interface: Antarmuka yang mudah digunakan dengan Gradio
- Comprehensive Analysis: Analisis mendalam dengan rekomendasi
📊 Models Used
- XGBoost: Gradient boosting model
- LightGBM: Light gradient boosting model
- CatBoost: Categorical boosting model
- LSTM: Long Short-Term Memory neural network
- Improved LSTM: Enhanced LSTM model
🔧 Input Features
- Personal Information: Age, Income, Employment Length
- Loan Information: Loan Amount, Interest Rate, Loan-to-Income Ratio
- Credit History: Credit History Length, Number of Credit Lines, Credit Utilization
- Payment History: Payment History Status, Delinquencies
📈 Output
- Risk Probability (0-100%)
- Risk Level (Low/Medium/High)
- Individual Model Predictions
- Recommendations
🛠️ Technology Stack
- Python 3.9+
- Gradio
- TensorFlow/Keras
- XGBoost, LightGBM, CatBoost
- Pandas, NumPy, Scikit-learn
📝 License
Apache License 2.0
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