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Issue:Intuitionistic fuzzy versions of K-NN method and their application to respiratory distress syndrome detection

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Title of paper: Intuitionistic fuzzy versions of K-NN method and their application to respiratory distress syndrome detection
Author(s):
Stefan Hadjitodorov
Department of Biomedical Informatics, Central Laboratory of Biomedical Engineering, Bulgarian Academy of Sciences, Acad. G. Bonchev Str. bl.105, 1113 Sofia, Bulgaria
Published in: "Notes on IFS", Volume 4 (1998) Number 4, pages 62—67
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Abstract: Intuitionistic fuzzy versions of one of the basic statistical nonparametrical methods, the K-NN method, are proposed. The inclusion of fuzzy information is made through modification of the distances by means of the pattern degrees of membership and nonmembership to the classes to which the reference pattern belongs. Thus for each of the labeled samples its typicalness and nontypicalness are taken into consideration. The versions are applied to Respiratory Distress Syndrome (RDS) detection.
Keywords: Pattern recognition; Fuzzy classification; Intuitionistic fuzzy sets; Fuzzy K-NN; Respiratory Distress Syndrome (RDS) detection.
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