Personalized Multitask Learning for Predicting Tomorrow's Mood, Stress, and Health

While accurately predicting mood and wellbeing could have a number of important clinical benefits, traditional machine learning (ML) methods frequently yield low performance in this domain. We posit that this is because a one-size-fits-all machine learning model is inherently ill-suited to predictin...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:IEEE transactions on affective computing 2020-04, Vol.11 (2), p.200-213
Hauptverfasser: Taylor, Sara, Jaques, Natasha, Nosakhare, Ehimwenma, Sano, Akane, Picard, Rosalind
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!