Projection to latent correlative structures, a dimension reduction strategy for spectral-based classification

Latent variables are used in chemometrics to reduce the dimension of the data. It is a crucial step with spectroscopic data where the number of explanatory variables can be very high. Principal component analysis (PCA) and partial least squares (PLS) are the most common. However, the resulting laten...

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Detalles Bibliográficos
Autores principales: Erny, Guillaume Laurent, Brito, Elsa, Pereira, Ana Bárbara, Bento-Silva, Andreia, Vaz Patto, Maria Carlota, Bronze, Maria Rosario
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society of Chemistry 2021
Materias:
Chemistry
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9040593/
https://www.ncbi.nlm.nih.gov/pubmed/35479572
http://dx.doi.org/10.1039/d1ra03359j

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9040593/
https://www.ncbi.nlm.nih.gov/pubmed/35479572
http://dx.doi.org/10.1039/d1ra03359j

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