@inbook{0636e79ffb784d5cadb69da7b774585f,

title = "Quality of rough approximation in multi-criteria classification problems",

abstract = "Dominance-based Rough Set Approach (DRSA) has been proposed to deal with multi-criteria classification problems, where data may be inconsistent with respect to the dominance principle. In this paper, we consider different measures of the quality of approximation, which is the value indicating how much inconsistent the decision table is. We begin with the classical definition, based on the relative number of inconsistent objects. Since this measure appears to be too restrictive in some cases, a new approach based on the concept of generalized decision is proposed. Finally, motivated by emerging problems in the presence of noisy data, the third measure based on the object reassignment is introduced. Properties of these measures are analysed in light of rough set theory.",

author = "K. Dembczynski and Salvatore Greco and W. Kotlowski and R. Slowinski",

year = "2006",

doi = "10.1007/11908029_34",

language = "English",

isbn = "9783540476931",

volume = "4259",

series = "Lecture notes in computer science",

publisher = "Springer",

number = "4259",

pages = "318--327",

editor = "Salvatore Greco and Y. Hata and S. Hirano and M. Inuiguchi and S. Miyamoto and H. Nguyen and R. Slowinski",

booktitle = "Rough sets and current trends in computing: proceedings of the 5th international conference",

edition = "4259",

}