Migrating from partial least squares discriminant analysis to artificial neural networks: a comparison of functionally equivalent visualisation and feature contribution tools using jupyter notebooks

INTRODUCTION: Metabolomics data is commonly modelled multivariately using partial least squares discriminant analysis (PLS-DA). Its success is primarily due to ease of interpretation, through projection to latent structures, and transparent assessment of feature importance using regression coefficie...

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Detalles Bibliográficos
Autores principales: Mendez, Kevin M., Broadhurst, David I., Reinke, Stacey N.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2020
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6974504/
https://www.ncbi.nlm.nih.gov/pubmed/31965332
http://dx.doi.org/10.1007/s11306-020-1640-0

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6974504/
https://www.ncbi.nlm.nih.gov/pubmed/31965332
http://dx.doi.org/10.1007/s11306-020-1640-0

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