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Discovey Science

Volume 1532 of the series Lecture Notes in Computer Science pp 244-255

Date:

Boosting Cost-Sensitive Trees

  • Kai Ming TingAffiliated withSchool of Computing and Mathematics, Deakin University
  • , Zijian ZhengAffiliated withSchool of Computing and Mathematics, Deakin University

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Abstract

This paper explores two techniques for boosting costsensitive trees. The two techniques differ in whether the misclassification cost information is utilized during training. We demonstrate that each of these techniques is good at different aspects of cost-sensitive classifications. We also show that both techniques provide a means to overcome the weaknesses of their base cost-sensitive tree induction algorithm