Selection of prototype rules: context searching via clustering.


Marcin Blachnik1 , Wlodzislaw Duch2,3 and Tadeusz Wieczorek1
1Division of Computer Methods, Department of Electrotechnology, The Silesian University of Technology, Katowice, Poland.
2School of Computer Engineering, Nanyang Technological University, Singapore.
3Department of Informatics, Nicolaus Copernicus University, Grudziadzka 5, 87-100 Torun, Poland.

Abstract.

Prototype-based rules are an interesting alternative to fuzzy and crisp logical rules, in many cases providing simpler, more accurate and more comprehensible description of the data. Such rules may be directly converted to fuzzy rules. A new algorithm for generation of prototype-based rules is introduced and a comparison with results obtained by neurofuzzy systems on a number of datasets provided.

Preprint for comments in PDF, 150 KB.

Reference: Blachnik M, Duch W, Wieczorek T, Selection of prototypes rules context searching via clustering. Lecture Notes in Artificial Intelligence, Vol. 4029 (2006) 573--582

BACK to the publications of W. Duch.
BACK to the on-line publications of the Department of Informatics, NCU.