Improving Multilabel Classification Model Performance in Imbalanced Datasets with Group-Level Undersampling
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F26%3A5Z2CGM53" target="_blank" >RIV/00216208:11320/26:5Z2CGM53 - isvavai.cz</a>
Result on the web
<a href="https://www.etasr.com/index.php/ETASR/article/view/10680" target="_blank" >https://www.etasr.com/index.php/ETASR/article/view/10680</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.48084/etasr.10680" target="_blank" >10.48084/etasr.10680</a>
Alternative languages
Result language
angličtina
Original language name
Improving Multilabel Classification Model Performance in Imbalanced Datasets with Group-Level Undersampling
Original language description
Received: 24 February 2025 | Revised: 18 April 2025 | Accepted: 8 May 2025 | Online: 2 August 2025Corresponding author: Danny Sebastian
Czech name
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Czech description
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Classification
Type
J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
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Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Engineering, Technology & Applied Science Research
ISSN
1792-8036
e-ISSN
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Volume of the periodical
15
Issue of the periodical within the volume
4
Country of publishing house
US - UNITED STATES
Number of pages
11
Pages from-to
24764-24774
UT code for WoS article
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EID of the result in the Scopus database
2-s2.0-105013115492