About: Evaluation framework of hierarchical clustering methods for binary data

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rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
rdfs:seeAlso	http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6421371&isnumber=6421298
Description	The article aims to evaluate hierarchical clustering methods according to their performance for binary data type. We explore the accuracy of ten hierarchical clustering methods by experimenting with ten different distance measures. The three types of well, poorly and very poorly separated clusters of binary data sets are generated by selecting the appropriate parameters for binomial distribution and Monte Carlo method. In order to evaluate the precision of clustering methods the binary data sets are transformed to distance matrices. The error level each method is explored in relationship to distance measures, cluster types and data distributions. The Complete linkage, Flexible-beta and Ward´s methods have best clustering performance for the case of two well separated clusters of binary data. The article aims to evaluate hierarchical clustering methods according to their performance for binary data type. We explore the accuracy of ten hierarchical clustering methods by experimenting with ten different distance measures. The three types of well, poorly and very poorly separated clusters of binary data sets are generated by selecting the appropriate parameters for binomial distribution and Monte Carlo method. In order to evaluate the precision of clustering methods the binary data sets are transformed to distance matrices. The error level each method is explored in relationship to distance measures, cluster types and data distributions. The Complete linkage, Flexible-beta and Ward´s methods have best clustering performance for the case of two well separated clusters of binary data. (en)
Title	Evaluation framework of hierarchical clustering methods for binary data Evaluation framework of hierarchical clustering methods for binary data (en)
skos:prefLabel	Evaluation framework of hierarchical clustering methods for binary data Evaluation framework of hierarchical clustering methods for binary data (en)
skos:notation	RIV/00216224:14330/12:00062299!RIV13-MSM-14330___
http://linked.open...avai/riv/aktivita	I P S
http://linked.open...avai/riv/aktivity	I, P(LA09016), S
http://linked.open...vai/riv/dodaniDat	2013
http://linked.open...aciTvurceVysledku	Kriksciuniene, Dalia
http://linked.open.../riv/druhVysledku	D - Článek ve sborníku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	Masarykova univerzita / Fakulta informatiky
http://linked.open...dnocenehoVysledku	135040
http://linked.open...ai/riv/idVysledku	RIV/00216224:14330/12:00062299
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	Cluster analysis; binary data; Monte Carlo simulation; distance matrix; hierarchical clustering (en)
http://linked.open.../riv/klicoveSlovo	distance matrix Cluster analysis binary data Monte Carlo simulation hierarchical clustering
http://linked.open...ontrolniKodProRIV	[E0AF5E10D592]
http://linked.open...v/mistoKonaniAkce	Pune, India
http://linked.open...i/riv/mistoVydani	Pune, India
http://linked.open...i/riv/nazevZdroje	Proceedings of 12th International Conference on Hybrid Intelligent Systems (HIS)
http://linked.open...in/vavai/riv/obor	IN
http://linked.open...ichTvurcuVysledku	1 (xsd:int)
http://linked.open...cetTvurcuVysledku	3 (xsd:int)
http://linked.open...vavai/riv/projekt	Czech Republic membership in the European Research Consortium for Informatics and Mathematics (ERCIM)
http://linked.open...UplatneniVysledku	2012
http://linked.open...iv/tvurceVysledku	Kriksciuniene, Dalia Sakalauskas, Virgilijus Tamasauskas, Darius
http://linked.open...vavai/riv/typAkce	WRD - Světová
http://linked.open.../riv/zahajeniAkce	2012-12-04 (xsd:date)
number of pages	6 (xsd:int)
http://bibframe.org/vocab/doi	10.1109/HIS.2012.6421371
http://purl.org/ne...btex#hasPublisher	IEEE
https://schema.org/isbn	9781467351140
http://localhost/t...ganizacniJednotka	14330

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