About: Classification by the Use of Decomposition of Correlation Integral

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rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	For estimating the value of the correlation dimension, a polynomial approximation of correlation integral is often used and then linear regression for logarithms of variables is applied. In this Chapter, we show that the correlation integral can be decomposed into functions each related to a particular point of data space. The essential difference is that the value of the exponent, which would correspond to the correlation dimension, differs in accordance to the position of the point in question. Moreover, we show that the multiplicative constant represents the probability density estimation at that point. This finding is used to construct a classifier. Tests with some data sets from the Machine Learning Repository show that this classifier can be very effective. For estimating the value of the correlation dimension, a polynomial approximation of correlation integral is often used and then linear regression for logarithms of variables is applied. In this Chapter, we show that the correlation integral can be decomposed into functions each related to a particular point of data space. The essential difference is that the value of the exponent, which would correspond to the correlation dimension, differs in accordance to the position of the point in question. Moreover, we show that the multiplicative constant represents the probability density estimation at that point. This finding is used to construct a classifier. Tests with some data sets from the Machine Learning Repository show that this classifier can be very effective. (en)
Title	Classification by the Use of Decomposition of Correlation Integral Classification by the Use of Decomposition of Correlation Integral (en)
skos:prefLabel	Classification by the Use of Decomposition of Correlation Integral Classification by the Use of Decomposition of Correlation Integral (en)
skos:notation	RIV/67985807:_____/09:00342904!RIV11-MSM-67985807
http://linked.open...avai/riv/aktivita	P Z
http://linked.open...avai/riv/aktivity	P(1M0567), Z(AV0Z10300504), Z(MSM6840770012)
http://linked.open...vai/riv/dodaniDat	2011
http://linked.open...aciTvurceVysledku	Jiřina, Marcel
http://linked.open.../riv/druhVysledku	C - Kapitola v knize
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	Ústav informatiky AV ČR, v. v. i.
http://linked.open...dnocenehoVysledku	307229
http://linked.open...ai/riv/idVysledku	RIV/67985807:_____/09:00342904
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	classification; multifractal; correlation dimension; distribution mapping exponent (en)
http://linked.open.../riv/klicoveSlovo	classification correlation dimension multifractal distribution mapping exponent
http://linked.open...ontrolniKodProRIV	[6FEB0BD3BB39]
http://linked.open...i/riv/mistoVydani	Berlin
http://linked.open...vEdiceCisloSvazku	Studies in Computational Intelligence, 205
http://linked.open...i/riv/nazevZdroje	Foundations of Computational Intelligence
http://linked.open...in/vavai/riv/obor	IN
http://linked.open...ichTvurcuVysledku	1 (xsd:int)
http://linked.open...v/pocetStranKnihy	378 (xsd:int)
http://linked.open...cetTvurcuVysledku	2 (xsd:int)
http://linked.open...vavai/riv/projekt	Centre for Applied Cybernetics
http://linked.open...UplatneniVysledku	2009
http://linked.open...iv/tvurceVysledku	Jiřina jr., M. Jiřina, Marcel
http://linked.open...n/vavai/riv/zamer	Informatika pro informační společnost: modely, algoritmy, aplikace Transdisciplinární výzkum v oblasti biomedicínského inženýrství II
number of pages	17 (xsd:int)
http://purl.org/ne...btex#hasPublisher	Springer-Verlag
https://schema.org/isbn	978-3-642-01535-9

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