ℝeal boosting a la Carte with an application to boosting oblique decision trees

Abstract

In the past ten years, boosting has become a major field of machine learning and classification. This paper brings contributions to its theory and algorithms. We first unify a well-known top-down decision tree induction algorithm due to [Kearns and Mansour, 1999], and discrete AdaBoost [Freund and Schapire, 1997], as two versions of a same higher-level boosting algorithm. It may be used as the basic building block to devise simple provable boosting algorithms for complex classifiers. We provide one example: the first boosting algorithm for Oblique Decision Trees, an algorithm which turns out to be simpler, faster and significantly more accurate than previous approaches. Show more