Cargando…

Machine learning enthusiasts should stick to the facts. Response to Morrison et al. (2022)

Detalles Bibliográficos
Autor principal: Biedermann, Alex
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9136307/
https://www.ncbi.nlm.nih.gov/pubmed/35647508
http://dx.doi.org/10.1016/j.fsisyn.2022.100229
_version_ 1784714150518194176
author Biedermann, Alex
author_facet Biedermann, Alex
author_sort Biedermann, Alex
collection PubMed
description
format Online
Article
Text
id pubmed-9136307
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Elsevier
record_format MEDLINE/PubMed
spelling pubmed-91363072022-05-28 Machine learning enthusiasts should stick to the facts. Response to Morrison et al. (2022) Biedermann, Alex Forensic Sci Int Synerg Perspectives and Opinion Elsevier 2022-05-10 /pmc/articles/PMC9136307/ /pubmed/35647508 http://dx.doi.org/10.1016/j.fsisyn.2022.100229 Text en © 2022 The Author https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Perspectives and Opinion
Biedermann, Alex
Machine learning enthusiasts should stick to the facts. Response to Morrison et al. (2022)
title Machine learning enthusiasts should stick to the facts. Response to Morrison et al. (2022)
title_full Machine learning enthusiasts should stick to the facts. Response to Morrison et al. (2022)
title_fullStr Machine learning enthusiasts should stick to the facts. Response to Morrison et al. (2022)
title_full_unstemmed Machine learning enthusiasts should stick to the facts. Response to Morrison et al. (2022)
title_short Machine learning enthusiasts should stick to the facts. Response to Morrison et al. (2022)
title_sort machine learning enthusiasts should stick to the facts. response to morrison et al. (2022)
topic Perspectives and Opinion
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9136307/
https://www.ncbi.nlm.nih.gov/pubmed/35647508
http://dx.doi.org/10.1016/j.fsisyn.2022.100229
work_keys_str_mv AT biedermannalex machinelearningenthusiastsshouldsticktothefactsresponsetomorrisonetal2022