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Rough-Fuzzy classifier modeling using data repository sets

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25410%2F14%3A39898896" target="_blank" >RIV/00216275:25410/14:39898896 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.1016/j.procs.2014.08.152" target="_blank" >http://dx.doi.org/10.1016/j.procs.2014.08.152</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1016/j.procs.2014.08.152" target="_blank" >10.1016/j.procs.2014.08.152</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Rough-Fuzzy classifier modeling using data repository sets

  • Original language description

    This paper reflects the trends of the past years based on the diffusion of various traditional approaches and methods when tackling new problems. Two components of the computational intelligence (CI) are applied, rough and fuzzy sets theory. These components permit one to operate with uncertainty data. The current knowledge in the investigated field is summarized and briefly explained. It also deals with uncertainty in an information system and the two approaches, the fuzzy sets (FSs) and rough sets theory (RST), for operating it. The proposal and implementation of a rough-fuzzy classifier (RFC) is modified. RFC uses the rules generated by RSTbox. The databases IRIS and WINE were chosen for verification. The classification results were compared with the results of other classification methods are applied on these databases. Finally, we summarized the presented problems. Based on the above stated facts it can be claimed that the proposed modified algorithm, RSTbox and RFC model are func

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2014

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Procedia Computer Science: Knowledge-Based and Intelligent Information & Engineering Systems 18th Annual Conference (KES-2014)

  • ISBN

  • ISSN

    1877-0509

  • e-ISSN

  • Number of pages

    9

  • Pages from-to

    701-709

  • Publisher name

    Elsevier Science BV

  • Place of publication

    Amsterdam

  • Event location

    Gdynia

  • Event date

    Sep 15, 2014

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article