Random forests for high-dimensional longitudinal data.
Stochastic mixed effects model
high-dimensional data
repeated measurements
tree-based methods
Journal
Statistical methods in medical research
ISSN: 1477-0334
Titre abrégé: Stat Methods Med Res
Pays: England
ID NLM: 9212457
Informations de publication
Date de publication:
01 2021
01 2021
Historique:
pubmed:
11
8
2020
medline:
3
8
2021
entrez:
11
8
2020
Statut:
ppublish
Résumé
Random forests are one of the state-of-the-art supervised machine learning methods and achieve good performance in high-dimensional settings where
Identifiants
pubmed: 32772626
doi: 10.1177/0962280220946080
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM