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Using Choquet integrals for kNN approximation and classification

Beliakov, Gleb and James, Simon 2008, Using Choquet integrals for kNN approximation and classification, in 2008 IEEE International Conference on Fuzzy Systems : proceedings : FUZZ-IEEE 2008, IEEE, Piscataway, N.J., pp. 1311-1317.

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Title Using Choquet integrals for kNN approximation and classification
Author(s) Beliakov, Gleb
James, Simon
Conference name IEEE International Conference on Fuzzy Systems (17th : 2008 : Hong Kong)
Conference location Hong Kong
Conference dates 1-6 June 2008
Title of proceedings 2008 IEEE International Conference on Fuzzy Systems : proceedings : FUZZ-IEEE 2008
Editor(s) Feng, Gary G.
Publication date 2008
Conference series International Conference on Fuzzy Systems
Start page 1311
End page 1317
Total pages 7
Publisher IEEE
Place of publication Piscataway, N.J.
Keyword(s) function approximation
fuzzy set theory
integral equations
learning (artificial intelligence)
pattern classification
Summary k-nearest neighbors (kNN) is a popular method for function approximation and classification. One drawback of this method is that the nearest neighbors can be all located on one side of the point in question x. An alternative natural neighbors method is expensive for more than three variables. In this paper we propose the use of the discrete Choquet integral for combining the values of the nearest neighbors so that redundant information is canceled out. We design a fuzzy measure based on location of the nearest neighbors, which favors neighbors located all around x.
Notes This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
ISBN 9781424418190
ISSN 1098-7584
Language eng
Field of Research 080108 Neural, Evolutionary and Fuzzy Computation
Socio Economic Objective 970101 Expanding Knowledge in the Mathematical Sciences
HERDC Research category E1 Full written paper - refereed
ERA Research output type E Conference publication
HERDC collection year 2008
Copyright notice ©2008, IEEE.
Persistent URL http://hdl.handle.net/10536/DRO/DU:30018288

Document type: Conference Paper
Collections: School of Engineering and Information Technology
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