- Tytuł:
- A Fuzzy If-Then Rule-Based Nonlinear Classifier
- Autorzy:
- Łęski, J.
- Powiązania:
- https://bibliotekanauki.pl/articles/908190.pdf
- Data publikacji:
- 2003
- Wydawca:
- Uniwersytet Zielonogórski. Oficyna Wydawnicza
- Tematy:
-
informatyka
classifier design
fuzzy if-then rules
generalization control
mixture of experts - Opis:
- This paper introduces a new classifier design method that is based on a modification of the classical Ho-Kashyap procedure. The proposed method uses the absolute error, rather than the squared error, to design a linear classifier. Additionally, easy control of the generalization ability and robustness to outliers are obtained. Next, an extension to a nonlinear classifier by the mixture-of-experts technique is presented. Each expert is represented by a fuzzy if-then rule in the Takagi-Sugeno-Kang form. Finally, examples are given to demonstrate the validity of the introduced method.
- Źródło:
-
International Journal of Applied Mathematics and Computer Science; 2003, 13, 2; 215-223
1641-876X
2083-8492 - Pojawia się w:
- International Journal of Applied Mathematics and Computer Science
- Dostawca treści:
- Biblioteka Nauki
Artykuł