Overview
A gradient boosting model for binary classification, trained on the Kaggle Titanic dataset to predict passenger survival from demographic and ticket features. Built with scikit-learn, XGBoost, and LightGBM, reporting 81.01% accuracy and 0.8088 AUC-ROC.
Installation
git clone https://github.com/coccinella-labs/lifeboat