Building a cost-constrained decision tree with multiple condition attributes

Authors:
Yen-Liang Chen;Chia-Chi Wu;Kwei Tang
Affiliations:
Department of Information Management, National Central University, No. 300, Jhongda Road, Chung-Li, Jhongli City 320, Taiwan, ROC;Department of Information Management, National Central University, No. 300, Jhongda Road, Chung-Li, Jhongli City 320, Taiwan, ROC;Krannert School of Management, Purdue University, West Lafayette, IN 47907, USA
Venue:
Information Sciences: an International Journal
Year:
2009

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Abstract

Costs are often an important part of the classification process. Cost factors have been taken into consideration in many previous studies regarding decision tree models. In this study, we also consider a cost-sensitive decision tree construction problem. We assume that there are test costs that must be paid to obtain the values of the decision attribute and that a record must be classified without exceeding the spending cost threshold. Unlike previous studies, however, in which records were classified with only a single condition attribute, in this study, we are able to simultaneously classify records with multiple condition attributes. An algorithm is developed to build a cost-constrained decision tree, which allows us to simultaneously classify multiple condition attributes. The experimental results show that our algorithm satisfactorily handles data with multiple condition attributes under different cost constraints.