… The AdaBoost algorithm of Freund and Schapire was the first practical boosting algorithm, …
This chapter aims to review some of the many perspectives and analyses of AdaBoost that …

… AdaBoost is successful not only because it is an effective … of AdaBoost in turn have fueled
innovation for ensemble learning research. In this paper, by following the trail of AdaBoost and …

… , while our algorithm remains as simple as AdaBoost. Our modification for … in AdaBoost. The
uncontrolled growth of the weights seems to be the root of the problems of AdaBoost and we …

… ADABOOST can be viewed as a constraint gradient descent in an error function with respect
to the margin. We find that ADABOOST … of the original ADABOOST algorithm to achieve a …

… The most and widely used boosting algorithm is AdaBoost and its later more effective
variations Gentle and Real AdaBoost. In this article we propose a new boosting algorithm, which …

… AdaBoost algorithm to the multi-class case without reducing it to multiple two-class problems.
Similar to AdaBoost … In addition, similar to the original AdaBoost algorithm for the two-class …

… of AdaBoost algorithm for feature selection, classifier learning and its relation with SVM, this
paper provided a brief introduction to the AdaBoost … based on AdaBoost boosting algorithm, …

A boosting algorithm, AdaBoost.RT, is proposed for regression problems. The idea is to filter
out examples with a relative estimation error that is higher than the pre-set threshold value, …

… AdaBoost … new AdaBoost algorithm with considering diversity in chapter 3. In chapter 4,
we compare performance between the real AdaBoost algorithm and the proposed Div-AdaBoost …

… The use of SVM (Support Vector Machine) as component classifier in AdaBoost may …
AdaBoost with strong component classifiers is not viable. In this paper, we shall show that AdaBoost …