TY  - CONF
ID  - moewes_unification_2008
T1  - Unification of Fuzzy {SVMs} and Rule Extraction Methods through imprecise Domain Knowledge
A1  - Moewes, Christian
A1  - Kruse, Rudolf
ED  - Verdegay, José Luis
ED  - Magdalena, Luis
ED  - Ojeda-Aciego, Manuel
TI  - Proceedings of the International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU-08)
Y1  - 2008
SP  - 1527
EP  - 1534
T2  - University of Málaga
CY  - Torremolinos (Málaga)
UR  - http://www.gimac.uma.es/ipmu08/proceedings/papers/203-Moewes.pdf
KW  - Binary Classification
KW  - Fuzzy Rules
KW  - fuzzy SVM
KW  - Support Vector Machine
N2  - In this paper, we want to motivate the combination of kernel-based methods with fuzzy rule extraction methods to describe uncertain domains by fuzzy models. We thus introduce and motivate the concept of a fuzzy support vector machine (FSVM) to incorporate impreciseness into kernel machines. Furthermore, we present the idea of a positive definite fuzzy classifier (PDFC), the rules of which are obtained by kernel-based models. We conclude with two vague conceptions to associate FSVM with PDFC to finally obtain understandable and meaningful fuzzy rules.
ER  -