This project investigates ensemble learning techniques, combining multiple models to enhance accuracy and robustness. It covers both basic methods (Max Voting, Averaging, Weighted Averaging) and advanced techniques (Stacking, Blending, Bagging, Boosting), aiming to improve predictive performance by addressing model weaknesses.
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Updated
Aug 11, 2024 - Jupyter Notebook