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An interval type-2 fuzzy K-nearest neighbor

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2 Author(s)
Rhee, F.C.-H. ; Dept. of Electron. Eng., Hanyang Univ., Ansan, South Korea ; Cheul Hwang

This paper presents an interval type-2 fuzzy K-nearest neighbor (NN) algorithm that is an extension of the type-1 fuzzy K-NN algorithm proposed in. In our proposed method, the membership values for each pattern vector are extended as interval type-2 fuzzy memberships by assigning uncertainty to the type-1 memberships. By doing so, the classification result obtained by the interval type-2 fuzzy K-NN is found to be more reasonable than that of the crisp and type-1 fuzzy K-NN. Experimental results are given to show the effectiveness of our method.

Published in:

Fuzzy Systems, 2003. FUZZ '03. The 12th IEEE International Conference on  (Volume:2 )

Date of Conference:

25-28 May 2003