Number of the records: 1  

Evaluation of Categorical Data Clustering

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    SYSNO ASEP0356106
    Document TypeC - Proceedings Paper (int. conf.)
    R&D Document TypeConference Paper
    TitleEvaluation of Categorical Data Clustering
    Author(s) Řezanková, H. (CZ)
    Löster, T. (CZ)
    Húsek, Dušan (UIVT-O) RID, SAI, ORCID
    Source TitleAdvances in Intelligent Web Mastering - 3. - Berlin : Springer, 2011 / Mugellini E. ; Szczepaniak P.S. ; Pettenati M.C. ; Sokhn M. - ISSN 1867-5662 - ISBN 978-3-642-18028-6
    Pagess. 173-182
    Number of pages10 s.
    ActionAWIC 2011. Atlantic Web Intelligence Conference /7./
    Event date26.01.2011-28.01.2011
    VEvent locationFribourg
    CountryCH - Switzerland
    Event typeWRD
    Languageeng - English
    CountryDE - Germany
    Keywordscluster analysis ; nominal variable ; determination of cluster numbers ; evaluation of clustering
    Subject RIVIN - Informatics, Computer Science
    R&D ProjectsGAP202/10/0262 GA ČR - Czech Science Foundation (CSF)
    GA205/09/1079 GA ČR - Czech Science Foundation (CSF)
    CEZAV0Z10300504 - UIVT-O (2005-2011)
    UT WOS000290421700018
    EID SCOPUS80052929337
    DOI10.1007/978-3-642-18029-3_18
    AnnotationMethods of cluster analysis are well known techniques of multivariate analysis used for many years. Their main applications concern clustering objects characterized by quantitative variables. For this case various coefficients for clustering evaluation and determination of cluster numbers have been proposed. However, in some areas, i.e., for segmentation of Internet users, the variables are often nominal or ordinal as their origin in questionnaire responses. That is why we are dealing with the evaluation criteria for the case of categorical variables here. The criteria based on variability measures are proposed. Instead of variance as a measure for quantitative variables, three measures for nominal variables are considered: the variability measure based on a modal frequency, Gini’s coefficient of mutability, and the entropy. The proposed evaluation criteria are applied to a real-dataset.
    WorkplaceInstitute of Computer Science
    ContactTereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800
    Year of Publishing2011
Number of the records: 1  

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