The Alternating Decision Tree Learning Algorithm

Abstract

1 INTRODUCTION The AdaBoost algorithm [7, 16] has recently proved to be an important component in practical learning algorithms. Two of the most successful combinations have been boosting decision trees and boosting stumps [6, 1, 13, 8]. Stumps are the simplest special case of decision trees which consist of a single decision node and two prediction leaves. Boosting decision trees learning algorithms, such as CART [2] and C4.5 [14], yields very good classifiers.