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Article

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Title

Learning vector quantization as an interpretable classifier for the detection of SARS-CoV-2 types based on their RNA sequences

Authors

[ 1 ] Instytut Informatyki, Wydział Informatyki i Telekomunikacji, Politechnika Poznańska | [ S ] student | [ P ] employee

Scientific discipline (Law 2.0)

[2.3] Information and communication technology

Year of publication

2022

Published in

Neural Computing and Applications

Journal year: 2022 | Journal volume: vol. 34 | Journal number: iss. 1

Article type

scientific article

Publication language

english

Keywords
EN
  • learning vector quantization
  • interpretable models
  • genomic sequence analysis
  • reject options
Date of online publication

27.04.2021

Pages (from - to)

67 - 78

DOI

10.1007/s00521-021-06018-2

URL

https://link.springer.com/article/10.1007%2Fs00521-021-06018-2

License type

CC BY (attribution alone)

Open Access Mode

czasopismo hybrydowe - umowa transformacyjna

Open Access Text Version

final published version

Date of Open Access to the publication

in press

Ministry points / journal

100

Impact Factor

6

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