https://github.com/rahulvictor12/german-bank-loan-defaulter-prediction
A machine learning project to predict loan defaults in a German bank's customer base. Using the German Credit Risk dataset, it explores key factors contributing to defaults and trains models like Random Forest, GBM, and XGBoost. Includes EDA, data processing, hyperparameter tuning, and model evaluation.
https://github.com/rahulvictor12/german-bank-loan-defaulter-prediction
accuracy ada-boost-classifier bagging categorical-encoding data-processing exploratory-data-analysis f1-score gbm gridsearchcv hyperparameter-tuning machine-learning missing-value-handling modelevaluation precision random-forest randomsearch-cv recall xgboost
Last synced: 2 months ago
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A machine learning project to predict loan defaults in a German bank's customer base. Using the German Credit Risk dataset, it explores key factors contributing to defaults and trains models like Random Forest, GBM, and XGBoost. Includes EDA, data processing, hyperparameter tuning, and model evaluation.
- Host: GitHub
- URL: https://github.com/rahulvictor12/german-bank-loan-defaulter-prediction
- Owner: rahulvictor12
- Created: 2024-11-24T08:18:19.000Z (5 months ago)
- Default Branch: main
- Last Pushed: 2024-11-24T08:24:44.000Z (5 months ago)
- Last Synced: 2025-01-08T08:48:41.383Z (4 months ago)
- Topics: accuracy, ada-boost-classifier, bagging, categorical-encoding, data-processing, exploratory-data-analysis, f1-score, gbm, gridsearchcv, hyperparameter-tuning, machine-learning, missing-value-handling, modelevaluation, precision, random-forest, randomsearch-cv, recall, xgboost
- Language: Jupyter Notebook
- Homepage:
- Size: 1.02 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0