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Applicability of Ordinal Sums of Conjunctive and Disjunctive Functions in Classification

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27510%2F21%3A10248253" target="_blank" >RIV/61989100:27510/21:10248253 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.atlantis-press.com/proceedings/ifsa-eusflat-agop-21" target="_blank" >https://www.atlantis-press.com/proceedings/ifsa-eusflat-agop-21</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.2991/asum.k.210827.081" target="_blank" >10.2991/asum.k.210827.081</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Applicability of Ordinal Sums of Conjunctive and Disjunctive Functions in Classification

  • Original language description

    Classification relies on the rules expressed by domain experts, or on the labeled attribute explaining the output classes. However, such information is not always available. In this work, we explore classification according to aggregation functions of mixed behaviour by the variability in ordinal sums of conjunctive and disjunctive functions. By this approach, entities are classified into three classes: yes, no and maybe including inclination to the classes yes and no. By the proposed approach, domain experts (or ordinal users) explain classification linguistically, without stating IF-THEN rules and labeled output. The applicability is illustrated by two examples. The discussion of the results and further research activities conclude the paper.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10200 - Computer and information sciences

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2021

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Atlantis Studies in Uncertainty Modelling. Volume 3

  • ISBN

    978-94-6239-423-0

  • ISSN

    2589-6644

  • e-ISSN

  • Number of pages

    6

  • Pages from-to

    602-607

  • Publisher name

    Atlantis Press

  • Place of publication

    Paris

  • Event location

    Bratislava

  • Event date

    Sep 19, 2021

  • Type of event by nationality

    EUR - Evropská akce

  • UT code for WoS article