Can We Trust Score Plots?

In this paper, we discuss the validity of using score plots of component models such as partial least squares regression, especially when these models are used for building classification models, and models derived from partial least squares regression for discriminant analysis (PLS-DA). Using examp...

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Detalles Bibliográficos
Autores principales: Bevilacqua, Marta, Bro, Rasmus
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Communication
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7408101/
https://www.ncbi.nlm.nih.gov/pubmed/32650451
http://dx.doi.org/10.3390/metabo10070278
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author Bevilacqua, Marta
Bro, Rasmus
author_facet Bevilacqua, Marta
Bro, Rasmus
author_sort Bevilacqua, Marta
collection PubMed
description In this paper, we discuss the validity of using score plots of component models such as partial least squares regression, especially when these models are used for building classification models, and models derived from partial least squares regression for discriminant analysis (PLS-DA). Using examples and simulations, it is shown that the currently accepted practice of showing score plots from calibration models may give misleading interpretations. It is suggested and shown that the problem can be solved by replacing the currently used calibrated score plots with cross-validated score plots.
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spelling pubmed-74081012020-08-25 Can We Trust Score Plots? Bevilacqua, Marta Bro, Rasmus Metabolites Communication In this paper, we discuss the validity of using score plots of component models such as partial least squares regression, especially when these models are used for building classification models, and models derived from partial least squares regression for discriminant analysis (PLS-DA). Using examples and simulations, it is shown that the currently accepted practice of showing score plots from calibration models may give misleading interpretations. It is suggested and shown that the problem can be solved by replacing the currently used calibrated score plots with cross-validated score plots. MDPI 2020-07-08 /pmc/articles/PMC7408101/ /pubmed/32650451 http://dx.doi.org/10.3390/metabo10070278 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Communication
Bevilacqua, Marta
Bro, Rasmus
Can We Trust Score Plots?
title Can We Trust Score Plots?
title_full Can We Trust Score Plots?
title_fullStr Can We Trust Score Plots?
title_full_unstemmed Can We Trust Score Plots?
title_short Can We Trust Score Plots?
title_sort can we trust score plots?
topic Communication
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7408101/
https://www.ncbi.nlm.nih.gov/pubmed/32650451
http://dx.doi.org/10.3390/metabo10070278
work_keys_str_mv AT bevilacquamarta canwetrustscoreplots
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