Author(s)

J. Hollmen, M. Skubacz & M. Taniguchi

Abstract

In data mining and in classification specifically, cost issues have been undervalued for a long time, although they are of crucial importance in real-world applications. Recently, however, cost issues have received growing attention, see for example [1,2,3]. Cost-sensitive classifiers are usually based on the assumption of constant misclassification costs between given classes, that is, the cost incurred when an object of class j is erroneously classified as belonging to class /. In many domains, the same type of error may have differing costs due to particular characteristics of objects to be classified. For example, loss caused by misclassifying credit card abuse as normal usage is dependent on the a

Keywords