Afficher la notice abrégée

dc.contributor.authorValencia García, Olga 
dc.contributor.authorOrtiz Fernández, Mª Cruz 
dc.contributor.authorSánchez Pastor, Mª Sagrario 
dc.contributor.authorSarabia Peinador, Luis Antonio 
dc.date.accessioned2021-10-22T12:28:05Z
dc.date.available2021-10-22T12:28:05Z
dc.date.issued2021-10
dc.identifier.issn0169-7439
dc.identifier.urihttp://hdl.handle.net/10259/6078
dc.description.abstractThe paper presents a new proposal for a single overall measure, the diagonal modified confusion entropy (DMCEN), to assess the performance of class-models jointly computed for several classes, a versatile index regarding sensitivity and specificity, and that supports class weighting. The characteristics of the proposed figure of merit are illustrated as against other usual performance measures and show how the index is more sensitive to the variations in the class-models than similar published indexes. Besides, a benchmark value representing a random modelling is also defined for DMCEN to be used as initial level to assess the quality of the built class-models. Furthermore, systematic comparisons have been conducted by using the degree of consistency C and the degree of discriminancy D when comparing the proposed DMCEN to the usual total efficiency (a geometric mean between sensitivity and specificity). Simulations show that, for a hundred thousand sensitivity/specificity matrices with four categories, C is almost 0.7 on average, well above the needed 0.5, and there is more than 62% probability that DMCEN detects differences when the total efficiency does not. Illustration of the application of the index is shown with an experimental data set with four categories.en
dc.description.sponsorshipSpanish Ministerio de Ciencia, Innovaci on y Universidades (AEI) and Consejería de Educación de la Junta de Castilla y León through projects CTQ2017-88894-R and BU052P20 respectively (both co-financed with European Regional Development Funds)es
dc.format.mimetypeapplication/pdf
dc.language.isoenges
dc.publisherElsevieres
dc.relation.ispartofChemometrics and Intelligent Laboratory Systems. 2021, V. 217, 104423es
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectSensitivityen
dc.subjectSpecificityen
dc.subjectClass-modelen
dc.subjectType I and Type II errorsen
dc.subjectEntropyen
dc.subjectBenchmarken
dc.subject.otherQuímica analíticaes
dc.subject.otherChemistry, Analyticen
dc.titleA modified entropy-based performance criterion for class-modelling with multiple classesen
dc.typeinfo:eu-repo/semantics/articlees
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.relation.publisherversionhttps://doi.org/10.1016/j.chemolab.2021.104423es
dc.identifier.doi10.1016/j.chemolab.2021.104423
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/CTQ2017-88894-R/ES/NUEVAS HERRAMIENTAS QUIMIOMETRICAS CON VARIABLES LATENTES PARA LA TOMA DE DECISIONES EN TECNOLOGIA ANALITICA DE PROCESOS Y EN CONTEXTOS REGULADOS DE SEGURIDAD ALIMENTARIAes
dc.relation.projectIDinfo:eu-repo/grantAgreement/Junta de Castilla y León//BU052P20//Nuevos desarrollos metodológicos del diseño de experimentos para análisis químicos, bioquímicos y en tecnología analítica de procesoses
dc.journal.titleChemometrics and Intelligent Laboratory Systemses
dc.volume.number217es
dc.page.initial104423es
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersiones


Fichier(s) constituant ce document

Thumbnail

Ce document figure dans la(les) collection(s) suivante(s)

Afficher la notice abrégée