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Using Singularity Exponent in Distance based Classifier
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SYSNO ASEP 0351724 Document Type C - Proceedings Paper (int. conf.) R&D Document Type Conference Paper Title Using Singularity Exponent in Distance based Classifier Author(s) Jiřina, Marcel (UIVT-O) SAI, RID
Jiřina jr., M. (CZ)Source Title Proceedings of the 2010 10th International Conference on Intelligent Systems Design and Applications. - Los Alamitos : IEEE, 2010 / Hassanien A.E. ; Abraham A. ; Marcelloni F. ; Hagras H. ; Antonelli M. ; Hong T.P. - ISBN 978-1-4244-8135-4 Pages s. 220-224 Number of pages 5 s. Action ISDA 2010. International Conference on Intelligent Systems Design and Applications /10./ Event date 29.11.2010-01.12.2010 VEvent location Cairo Country EG - Egypt Event type WRD Language eng - English Country US - United States Keywords singularity exponent ; nearest neighbor ; classifier Subject RIV IN - Informatics, Computer Science R&D Projects 1M0567 GA MŠMT - Ministry of Education, Youth and Sports (MEYS) CEZ AV0Z10300504 - UIVT-O (2005-2011) EID SCOPUS 79851492856 DOI 10.1109/ISDA.2010.5687263 Annotation The paper deals with using so called singularity exponent in a classifier that is based on ordered distances of patterns to a given (classified) pattern. The approximation of probability distribution mapping function of the distribution of points from the viewpoint of distances from a given point in a form of a suitable power (exponent) of a distance is presented together with a way how to state it. A classifier utilizing knowledge about explored data distribution in a space and a suggested expression of the exponent is presented. Experimental results on both synthetic and real-life data show interesting behavior (classification accuracy) of the classifier in comparison with other well-known classifiers. Workplace Institute of Computer Science Contact Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800 Year of Publishing 2011
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