A comparative evaluation of the generalised predictive ability of eight machine learning algorithms across ten clinical metabolomics data sets for binary classification

INTRODUCTION: Metabolomics is increasingly being used in the clinical setting for disease diagnosis, prognosis and risk prediction. Machine learning algorithms are particularly important in the construction of multivariate metabolite prediction. Historically, partial least squares (PLS) regression h...

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Detalles Bibliográficos
Autores principales: Mendez, Kevin M., Reinke, Stacey N., Broadhurst, David I.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2019
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6856029/
https://www.ncbi.nlm.nih.gov/pubmed/31728648
http://dx.doi.org/10.1007/s11306-019-1612-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6856029/
https://www.ncbi.nlm.nih.gov/pubmed/31728648
http://dx.doi.org/10.1007/s11306-019-1612-4

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