Applicability of Ordinal Sums of Conjunctive and Disjunctive Functions in Classification
Result 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.
Keywords
Ordinal sumsConjunctive functionsDisjunctive functionsAveraging functionsClassification
The result's identifiers
Result code in IS VaVaI
Result on the web
https://www.atlantis-press.com/proceedings/ifsa-eusflat-agop-21
DOI - Digital Object Identifier
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
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Czech description
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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
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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
—
Basic information
Result type
D - Article in proceedings
OECD FORD
Computer and information sciences
Year of implementation
2021