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An experimental evaluation of some classification methods

Michael Doumpos, Zopounidis Konstantinos, Chatzi E.

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URIhttp://purl.tuc.gr/dl/dias/7D9E4380-B83E-4DAF-B5DA-B1B3D879CD03-
Identifierhttp://link.springer.com/article/10.1007/s10898-005-6152-y-
Identifierhttps://doi.org/10.1007/s10898-005-6152-y-
Languageen-
Extent18 pagesen
TitleAn experimental evaluation of some classification methodsen
CreatorMichael Doumposen
CreatorΔουμπος Μιχαληςel
CreatorZopounidis Konstantinosen
CreatorΖοπουνιδης Κωνσταντινοςel
CreatorChatzi E.en
PublisherSpringer Verlagen
Content SummaryThe classification problem is of major importance to a plethora of research fields. The outgrowth in the development of classification methods has led to the development of several techniques. The objective of this research is to provide some insight on the relative performance of some well-known classification methods, through an experimental analysis covering data sets with different characteristics. The methods used in the analysis include statistical techniques, machine learning methods and multicriteria decision aid. The results of the study can be used to support the design of classification systems and the identification of the proper methods that could be used given the data characteristics.en
Type of ItemPeer-Reviewed Journal Publicationen
Type of ItemΔημοσίευση σε Περιοδικό με Κριτέςel
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2015-11-18-
Date of Publication2006-
SubjectMachine learningen
SubjectClassification en
SubjectMonte Carlo simulation en
SubjectMulticriteria decision aid en
SubjectStatistical techniquesen
Bibliographic CitationM. Doumpos, E. Chatzi and C. Zopounidis, "An experimental evaluation of some classification methods," J. Global Optimizat., vol. 36, no. 1, pp. 33-50, Sep. 2006. doi:10.1007/s10898-005-6152-yen

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