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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...

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Podrobná bibliografie
Vydáno v:IEEE Trans Affect Comput
Hlavní autoři: Taylor, Sara, Jaques, Natasha, Nosakhare, Ehimwenma, Sano, Akane, Picard, Rosalind
Médium: Artigo
Jazyk:Inglês
Vydáno: 2017
Témata:
On-line přístup:https://ncbi.nlm.nih.gov/pmc/articles/PMC7266106/
https://ncbi.nlm.nih.gov/pubmed/32489521
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/TAFFC.2017.2784832
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