A comparison of classical and machine learning-based phenotype prediction methods on simulated data and three plant species

Titel:: A comparison of classical and machine learning-based phenotype prediction methods on simulated data and three plant species
Dokumenttyp:: Zeitschriftenaufsatz
Autor(en):: John, Maura; Haselbeck, Florian; Dass, Rupashree; Malisi, Christoph; Ricca, Patrizia; Dreischer, Christian; Schultheiss, Sebastian J.; Grimm, Dominik G.
Zeitschriftentitel:: Frontiers in Plant Science
Jahr:: 2022
Band / Volume:: 13
Reviewed:: ja
Volltext / DOI:: doi:10.3389/fpls.2022.932512
Verlag / Institution:: Frontiers Media SA
E-ISSN:: 1664-462X
Status:: Erstveröffentlichung
Publikationsdatum:: 04.11.2022
CC-Lizenz:: by, http://creativecommons.org/licenses/by/4.0

BibTeX

Vorkommen: