Machine Learning 32: AdaBoost Analysis

We continue our study of AdaBoost and prove that if the base learning algorithm used in each round has an advantage over random guessing, then after enough iterations, AdaBoost returns a classifier that perfectly classifies the training data. We also theoretically justify the choice of weights in the AdaBoost algorithm.