Additive logistic regression: a statistical view of boosting (With discussion and a rejoinder by the authors)
Additive logistic regression: a statistical view of boosting (With discussion and a rejoinder by the authors)
Boosting is one of the most important recent developments in classification methodology. Boosting works by sequentially applying a classification algorithm to reweighted versions of the training data and then taking a weighted majority vote of the sequence of classifiers thus produced. For many classification algorithms, this simple strategy results in …