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https://github.com/ata-turhan/titanic-survival-prediction
A comprehensive solution for the Kaggle Titanic Challenge, featuring advanced data exploration, feature engineering, model training, and explainable AI techniques. Includes Logistic Regression, RandomForest, XGBoost, and Stacked Ensembles with SHAP and permutation importance for model interpretability.
https://github.com/ata-turhan/titanic-survival-prediction
classification kaggle python shap xgboost
Last synced: 11 days ago
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A comprehensive solution for the Kaggle Titanic Challenge, featuring advanced data exploration, feature engineering, model training, and explainable AI techniques. Includes Logistic Regression, RandomForest, XGBoost, and Stacked Ensembles with SHAP and permutation importance for model interpretability.
- Host: GitHub
- URL: https://github.com/ata-turhan/titanic-survival-prediction
- Owner: ata-turhan
- License: mit
- Created: 2024-10-05T17:49:46.000Z (3 months ago)
- Default Branch: main
- Last Pushed: 2024-11-20T03:47:15.000Z (about 2 months ago)
- Last Synced: 2024-11-20T04:21:07.204Z (about 2 months ago)
- Topics: classification, kaggle, python, shap, xgboost
- Language: Jupyter Notebook
- Homepage:
- Size: 563 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0