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dc.contributor.author
Allegrini, Franco
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dc.contributor.author
Olivieri, Alejandro Cesar
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dc.date.available
2023-07-17T15:43:24Z
dc.date.issued
2022-09-11
dc.identifier.citation
Allegrini, Franco; Olivieri, Alejandro Cesar; Linear or non-linear multivariate calibration models? That is the question; Elsevier Science; Analytica Chimica Acta; 1226; 11-9-2022; 1-6
dc.identifier.issn
0003-2670
dc.identifier.uri
http://hdl.handle.net/11336/204191
dc.description.abstract
Concepts from data science, machine learning, deep learning and artificial neural networks are spreading in many disciplines. The general idea is to exploit the power of statistical tools to interpret complex and, in many cases, non-linear data. Specifically in analytical chemistry, many chemometrics tools are being developed. However, they tend to get more complex without necessarily improving the prediction ability, which conspires against parsimony. In this report, we show how non-linear analytical data sets can be solved with equal or better efficiency by easily interpretable modified linear models, based on the concept of local sample selection before model building. The latter activity is conducted by choosing a sub-set of samples located in the neighborhood of each unknown sample in the space spanned by the latent variables. Two experimental examples related to the use of near infrared spectroscopy for the analysis of target properties in food samples are examined. The comparison with seemingly more complex chemometric models reveals that local regression is able to achieve similar analytical performance, with considerably less computational burden.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Elsevier Science
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dc.rights
info:eu-repo/semantics/restrictedAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
ARTIFICIAL NEURAL NETWORKS
dc.subject
LOCAL PARTIAL LEAST-SQUARES
dc.subject
NEAR INFRARED SPECTROSCOPY
dc.subject
NON-LINEAR SYSTEMS
dc.subject.classification
Química Analítica
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dc.subject.classification
Ciencias Químicas
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dc.subject.classification
CIENCIAS NATURALES Y EXACTAS
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dc.title
Linear or non-linear multivariate calibration models? That is the question
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2023-07-10T10:41:49Z
dc.journal.volume
1226
dc.journal.pagination
1-6
dc.journal.pais
Países Bajos
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dc.journal.ciudad
Amsterdam
dc.description.fil
Fil: Allegrini, Franco. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Química Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Química Rosario; Argentina
dc.description.fil
Fil: Olivieri, Alejandro Cesar. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Química Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Química Rosario; Argentina
dc.journal.title
Analytica Chimica Acta
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dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0003267022008194
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1016/j.aca.2022.340248
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