When Analytic Calculus Cracks AdaBoost Code

The principle of boosting in supervised learning involves combining multiple weak classifiers to obtain a stronger classifier. AdaBoost has the reputation to be a perfect example of this approach.
This study analyzes the (two classes) AdaBoost procedure implemented in scikit-learn.
This paper shows that AdaBoost is an algorithm in name only, as the resulting combination of weak classifiers can be explicitly calculated using a truth table.
Indeed, using a logical analysis of the training set with weak classifiers constructing a …

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