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Rough sets based rule induction and multivariate statistical classification: A simulation study

Zopounidis Konstantinos, Doumpos, Michael

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URIhttp://purl.tuc.gr/dl/dias/463B6702-DFE3-4854-9012-C2E19EA7A068-
Identifierhttps://doi.org/10.1023/A:1015588600700-
Languageen-
Extent15 pages en
TitleRough sets based rule induction and multivariate statistical classification: A simulation studyen
CreatorZopounidis Konstantinosen
CreatorΖοπουνιδης Κωνσταντινοςel
CreatorDoumpos, Michaelen
PublisherKluweren
Content SummaryThe classification of a set of objects into predefined homogenous groups is a problem with major practical interest in many fields. Over the past two decades several non-parametric approaches have been developed to address the classification problem, originating from several scientific fields. This paper is focused on the rough sets approach and the investigation of its performance as opposed to traditional multivariate statistical classification procedures, namely the linear discriminant analysis, the quadratic discriminant analysis and the logit analysis. For this purpose an extensive Monte Carlo simulation is conducted to examine the performance of these methods under different data conditions.en
Type of ItemPeer-Reviewed Journal Publicationen
Type of ItemΔημοσίευση σε Περιοδικό με Κριτέςel
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2015-10-27-
Date of Publication2002-
SubjectEconomicsen
Bibliographic CitationM. Doumpos, C. Zopounidis ," Rough sets based rule induction and multivariate statistical classification: A simulation study," Comput. Econ., vol. 19, no. 3,pp. 287-301,Jun. 2002.doi:10.1023/A:1015588600700en

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