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Class modelling by Soft Independent Modelling of Class Analogy: why, when, how? A tutorial.
Vitale, Raffaele; Cocchi, Marina; Biancolillo, Alessandra; Ruckebusch, Cyril; Marini, Federico.
Afiliación
  • Vitale R; U. Lille, CNRS, LASIRE, Laboratoire Avancé de Spectroscopie pour les Interactions, la Réactivité et l'Environnement, Cité Scientifique, F-59000 Lille, France. Electronic address: raffaele.vitale@univ-lille.fr.
  • Cocchi M; Dipartimento di Scienze Chimiche e Geologiche, Università degli Studi di Modena e Reggio Emilia, Via Giuseppe Campi 103, 41125, Modena, Italy.
  • Biancolillo A; Dipartimento di Scienze Fisiche e Chimiche, Università degli Studi dell'Aquila, Via Vetoio, 67100, L'Aquila, Italy.
  • Ruckebusch C; U. Lille, CNRS, LASIRE, Laboratoire Avancé de Spectroscopie pour les Interactions, la Réactivité et l'Environnement, Cité Scientifique, F-59000 Lille, France.
  • Marini F; Dipartimento di Chimica, Università degli Studi di Roma "La Sapienza", Piazzale Aldo Moro 5, 00185, Roma, Italy.
Anal Chim Acta ; 1270: 341304, 2023 Aug 22.
Article en En | MEDLINE | ID: mdl-37311606
ABSTRACT
This article contains a comprehensive tutorial on classification by means of Soft Independent Modelling of Class Analogy (SIMCA). Such a tutorial was conceived in an attempt to offer pragmatic guidelines for a sensible and correct utilisation of this tool as well as answers to three basic questions "why employing SIMCA?", "when employing SIMCA?" and "how employing/not employing SIMCA?". With this purpose in mind, the following points are here addressed i) the mathematical and statistical fundamentals of the SIMCA approach are presented; ii) distinct variants of the original SIMCA algorithm are thoroughly described and compared in two different case-studies; iii) a flowchart outlining how to fine-tune the parameters of a SIMCA model for achieving an optimal performance is provided; iv) figures of merit and graphical tools for SIMCA model assessment are illustrated and v) computational details and rational suggestions about SIMCA model validation are given. Moreover, a novel Matlab toolbox, which encompasses routines and functions for running and contrasting all the aforementioned SIMCA versions is also made available.
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Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Año: 2023 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Año: 2023 Tipo del documento: Article