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Article


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

2021

Published in

Neural Computing and Applications

Journal year: 2021 | Journal volume: in press

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

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

Points of MNiSW / journal

100.0

Points of MNiSW / journal in years 2017-2021

100.0

Impact Factor

5.606 [List 2020]