PROCEEDINGS IPMU '08
Unification of Fuzzy SVMs and Rule Extraction Methods through imprecise Domain Knowledge
Christian Moewes, Rudolf Kruse.
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.
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