• DocumentCode
    2465331
  • Title

    A pattern classifier for interval-valued data based on multinomial logistic regression model

  • Author

    de Barros, A.P. ; de Assis Tenorio de Carvalho, F. ; de Andrade Lima Neto, E.

  • Author_Institution
    Inst. Fed. de Educ., Cienc. e Tecnol. da Paraiba, João Pessoa, Brazil
  • fYear
    2012
  • fDate
    14-17 Oct. 2012
  • Firstpage
    541
  • Lastpage
    546
  • Abstract
    Interval-valued data arise in practical situations such as recording monthly interval temperatures at meteorological stations, daily interval stock prices, etc. This paper introduces a multinomial logistic regression method for interval-valued data in order to classify items described by interval-valued variables into a pre-defined number of a priori classes. Applications of the proposed approach on real as well as synthetic interval-valued data sets showed the usefulness of this approach.
  • Keywords
    pattern classification; regression analysis; interval-valued variables; item classification; multinomial logistic regression model; pattern classifier; real interval-valued data sets; synthetic interval-valued data sets; Data analysis; Data models; Databases; Error analysis; Logistics; Mathematical model; Vectors; Multinomial logistic regression; interval-valued data; symbolic data analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man, and Cybernetics (SMC), 2012 IEEE International Conference on
  • Conference_Location
    Seoul
  • Print_ISBN
    978-1-4673-1713-9
  • Electronic_ISBN
    978-1-4673-1712-2
  • Type

    conf

  • DOI
    10.1109/ICSMC.2012.6377781
  • Filename
    6377781
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2465331