Discussing cluster shapes of fuzzy classifiers

Author

Nürnberger, Andreas ; Klose, Aljoscha ; Kruse, Rudolf

Author_Institution

Fac. of Comput. Sci., Magdeburg Univ., Germany

fYear

1999

fDate

36342

Firstpage

546

Lastpage

550

Abstract

Fuzzy classification rules are widely considered a well-suited representation of classification knowledge, as they allow readable and interpretable rule bases. The goal of the paper is to discuss the shapes of the resulting classification borders and thus which class distributions can be represented by such classification systems. 2D and 3D visualizations are used to illustrate the cluster shapes and the borders between distinct classes. Furthermore, general hints concerning the shape of higher dimensional clusters are given

Keywords

data visualisation; fuzzy set theory; knowledge based systems; knowledge representation; pattern classification; 3D visualizations; class distributions; classification borders; classification knowledge representation; classification systems; cluster shapes; fuzzy classification rules; fuzzy classifiers; higher dimensional clusters; interpretable rule bases; Computer science; Electronic mail; Fuzzy sets; Fuzzy systems; Humans; Prototypes; Shape; Uncertainty; Visualization;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Information Processing Society, 1999. NAFIPS. 18th International Conference of the North American

Conference_Location

New York, NY

Print_ISBN

0-7803-5211-4

Type

conf

DOI

10.1109/NAFIPS.1999.781753

Filename

781753