About: Separation in Data Mining Based on Fractal Nature of Data

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An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

Attributes	Values
rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
rdfs:seeAlso	http://sdiwc.net/digital-library/separation-in-data-mining-based-on-fractal-nature-of-data.html
Description	The separation of the searched data from the rest is an important task in data mining. Three separation/classification methods are presented. We use a singularity exponent in classifiers that are based on distances of patterns to a given (classified) pattern. The approximation of so called probability distribution mapping function of the distribution of points from the viewpoint of distances from a given point in the form of a scaling exponent power of a distance is presented together with a way how to state it. Considering data as points in a metric space, three methods are based on transformed distances of neighbors of a given point in a multidimensional space via functions that use different estimates of scaling exponent. Classifiers – data separators utilizing knowledge about explored data distribution in a space and suggested expressions of the scaling exponent are presented. Experimental results on both synthetic and real-life data show interesting behavior (classification accuracy) of classifiers in comparison with other well-known approaches. The separation of the searched data from the rest is an important task in data mining. Three separation/classification methods are presented. We use a singularity exponent in classifiers that are based on distances of patterns to a given (classified) pattern. The approximation of so called probability distribution mapping function of the distribution of points from the viewpoint of distances from a given point in the form of a scaling exponent power of a distance is presented together with a way how to state it. Considering data as points in a metric space, three methods are based on transformed distances of neighbors of a given point in a multidimensional space via functions that use different estimates of scaling exponent. Classifiers – data separators utilizing knowledge about explored data distribution in a space and suggested expressions of the scaling exponent are presented. Experimental results on both synthetic and real-life data show interesting behavior (classification accuracy) of classifiers in comparison with other well-known approaches. (en)
Title	Separation in Data Mining Based on Fractal Nature of Data Separation in Data Mining Based on Fractal Nature of Data (en)
skos:prefLabel	Separation in Data Mining Based on Fractal Nature of Data Separation in Data Mining Based on Fractal Nature of Data (en)
skos:notation	RIV/67985807:_____/13:00393276!RIV14-AV0-67985807
http://linked.open...avai/riv/aktivita	I
http://linked.open...avai/riv/aktivity	I
http://linked.open...iv/cisloPeriodika	1
http://linked.open...vai/riv/dodaniDat	2014
http://linked.open...aciTvurceVysledku	Jiřina, Marcel
http://linked.open.../riv/druhVysledku	J - Článek v odborném periodiku
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	104730
http://linked.open...ai/riv/idVysledku	RIV/67985807:_____/13:00393276
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	nearest neighbor; fractal set; multifractal; IINC method; correlation dimension (en)
http://linked.open.../riv/klicoveSlovo	correlation dimension fractal set IINC method multifractal nearest neighbor
http://linked.open...odStatuVydavatele	HK - Zvláštní administrativní oblast Čínské lidové republiky Hongkong
http://linked.open...ontrolniKodProRIV	[65F48BB14564]
http://linked.open...i/riv/nazevZdroje	International Journal of Digital Information and Wireless Communications
http://linked.open...in/vavai/riv/obor	JC
http://linked.open...ichTvurcuVysledku	1 (xsd:int)
http://linked.open...cetTvurcuVysledku	2 (xsd:int)
http://linked.open...UplatneniVysledku	2013
http://linked.open...v/svazekPeriodika	3
http://linked.open...iv/tvurceVysledku	Jiřina jr., M. Jiřina, Marcel
issn	2225-658X
number of pages	17 (xsd:int)

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