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Issue:K-NN intuitionistic fuzzy classifier

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Title of paper: k-NN intuitionistic fuzzy classifier
Author(s):
Eulalia Szmidt     0000-0003-2192-6905
Systems Research Institute, Polish Academy of Sciences, ul. Newelska 6, 01-447 Warsaw, Poland
WIT Academy, ul. Newelska 6, 01-447 Warsaw, Poland
szmidt@ibspan.waw.pl
Janusz Kacprzyk     0000-0003-4187-5877
Systems Research Institute, Polish Academy of Sciences, ul. Newelska 6, 01-447 Warsaw, Poland
WIT Academy, ul. Newelska 6, 01-447 Warsaw, Poland
kacprzyk@ibspan.waw.pl
Paweł Bujnowski     0000-0001-9215-0046
Systems Research Institute, Polish Academy of Sciences, ul. Newelska 6, 01-447 Warsaw, Poland
pbujno@ibspan.waw.pl
Published in: Notes on Intuitionistic Fuzzy Sets, Volume 31 (2025), Number 4, pages 496–510
DOI: https://doi.org/10.7546/nifs.2025.31.4.496-510
Download:  PDF (241  Kb, File info)
Abstract: The k-NN (k-Nearest Neighbor) classifier is one of the commonly used classifiers. We present a modification of this classifier based on Atanassov's intuitionistic fuzzy sets (IFSs, for short). We show, using benchmark data from UCI Machine Learning Repository, that the classifier we propose achieves very good results.
Keywords: Intuitionistic fuzzy sets, Classification, k-NN classifier.
AMS Classification: 03E72.
References:
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