Assessing rough classifiers

Journal article

Peters, Georg. (2015). Assessing rough classifiers. Fundamenta Informaticae. 137, pp. 493 - 515. https://doi.org/10.3233/FI-2015-1191
AuthorsPeters, Georg
Abstract

Since its introduction a prime area of application of rough sets theory has been in the field of classification. In this area rough sets theory provides a powerful toolbox of methods to deal with incomplete and contradicting information. Obviously, the assessment of the obtained classification results is of crucial importance. In our paper, we propose and evaluate some rough performance indices to evaluated the quality of bi- and multinomial classifiers. To illustrate their characteristics we perform comparative experiments on a synthetically generated data set.

Year2015
JournalFundamenta Informaticae
Journal citation137, pp. 493 - 515
ISSN0169-2968
Digital Object Identifier (DOI)https://doi.org/10.3233/FI-2015-1191
Page range493 - 515
Research GroupSchool of Arts
Publisher's version
File Access Level
Controlled
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