Shen, Chunhua; Li, Hanxi
We study boosting algorithms from a new perspective. We show that the Lagrange dual problems of l1-norm-regularized AdaBoost, LogitBoost, and soft-margin LPBoost with generalized hinge loss are all entropy maximization problems. By looking at the dual problems of these boosting algorithms, we show that the success of boosting algorithms can be understood in terms of maintaining a better margin distribution by maximizing margins and at the same time controlling the margin variance. We also...[Show more]
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