Model selection for metabolomics: predicting diagnosis of coronary artery disease using automated machine learning

MOTIVATION: Selecting the optimal machine learning (ML) model for a given dataset is often challenging. Automated ML (AutoML) has emerged as a powerful tool for enabling the automatic selection of ML methods and parameter settings for the prediction of biomedical endpoints. Here, we apply the tree-b...

Descrizione completa

Salvato in:
Dettagli Bibliografici
Pubblicato in:Bioinformatics
Autori principali: Orlenko, Alena, Kofink, Daniel, Lyytikäinen, Leo-Pekka, Nikus, Kjell, Mishra, Pashupati, Kuukasjärvi, Pekka, Karhunen, Pekka J, Kähönen, Mika, Laurikka, Jari O, Lehtimäki, Terho, Asselbergs, Folkert W, Moore, Jason H
Natura: Artigo
Lingua:Inglês
Pubblicazione: Oxford University Press 2019
Soggetti:
Original Papers
Accesso online:https://ncbi.nlm.nih.gov/pmc/articles/PMC7703753/
https://ncbi.nlm.nih.gov/pubmed/31702773
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/bioinformatics/btz796
Tags: Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne! !

Documenti analoghi