Understanding AdaBoost Classifier: Geometric Intuition, Step-by-Step Process, and Practical Implementation
AdaBoost (Adaptive Boosting) is one of the most popular machine learning algorithms for boosting. It builds a strong classifier by combining multiple weak classifiers, typically decision stumps (shallow decision trees). This post will provide an in-depth understanding of AdaBoost, including its geometric intuition, step-by-step working, implementation from scratch, hyperparameter tuning, and a comparison with bagging … Read more