A Bagging Method using Decision Trees in the Role of Base Classifiers
Kristína Machová, Peter Bednár · 2006
Abstract: This paper describes a set of experiments with bagging – a method, which can improve results of classification algorithms. Our use of this method aims at classification algorithms generating decision trees. Results of performance tests focused on the use of the bagging method on binary decision trees are presented. The minimum number of decision trees, which enables an improvement of the classification performed by the bagging method was found. The tests were carried out using the Reuters 21578 collection of documents as well as documents from an internet portal of TV broadcasting company Markíza.