PROCEEDINGS IPMU '08
A Type 2 Fuzzy C-Regression Method
Asli Celikyilmaz and I. Burhan Turksen.
This paper presents a type-2 genetic
fuzzy inference system based on fuzzy
c-regression method clustering
algorithm, to identify uncertainties in
hyperplane shaped fuzzy clusters. The
uncertainty in learning parameters of
the new system is identified by type-2
fuzzy sets. Genetic algorithm is used to
optimize the secondary membership
grades of the type-2 fuzzy sets.
Transductive reasoning, instead of
inductive reasoning, is used to develop
a local model for every new vector,
based on some closest vectors from the
given database. This study is novel
because it presents a new methodology
to identify type-2 fuzzy sets. The
results of comparative experiments on
financial forecasting problem domain
are encouraging.
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