dc.creator | Blanquero Bravo, Rafael | es |
dc.creator | Carrizosa Priego, Emilio José | es |
dc.creator | Jiménez Cordero, María Asunción | es |
dc.creator | Martín Barragán, Belén | es |
dc.date.accessioned | 2021-04-26T13:14:58Z | |
dc.date.available | 2021-04-26T13:14:58Z | |
dc.date.issued | 2020-07-19 | |
dc.identifier.citation | Blanquero Bravo, R., Carrizosa Priego, E.J., Jiménez Cordero, M.A. y Martín Barragán, B. (2020). Selection of time instants and intervals with Support Vector Regression for multivariate functional data. Computers & Operations Research, 123, 105050 - 1-105050 - 24. | |
dc.identifier.issn | 0305-0548 | es |
dc.identifier.issn | 1873-765X | es |
dc.identifier.uri | https://hdl.handle.net/11441/107836 | |
dc.description.abstract | When continuously monitoring processes over time, data is collected along a whole period, from which
only certain time instants and certain time intervals may play a crucial role in the data analysis. We
develop a method that addresses the problem of selecting a finite and small set of short intervals (or
instants) able to capture the information needed to predict a response variable from multivariate functional
data using Support Vector Regression (SVR).
In addition to improving interpretability, storage requirements, and monitoring cost, feature selection
can potentially reduce overfitting by mitigating data autocorrelation. We propose a continuous optimization
algorithm to fit the SVR parameters and select intervals and instants. Our approach takes advantage
of the functional nature of the data by formulating a new bilevel optimization problem that integrates
selection of intervals and instants, tuning of some key SVR parameters and fitting the SVR. We illustrate
the usefulness of our proposal in some benchmark data sets. | es |
dc.format | application/pdf | es |
dc.format.extent | 24 p. | es |
dc.language.iso | eng | es |
dc.publisher | PERGAMON-ELSEVIER SCIENCE LTD | es |
dc.relation.ispartof | Computers & Operations Research, 123, 105050 - 1-105050 - 24. | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Machine learning | es |
dc.subject | Functional regression | es |
dc.subject | Support Vector Regression | es |
dc.subject | Time interval selection | es |
dc.title | Selection of time instants and intervals with Support Vector Regression for multivariate functional data | es |
dc.type | info:eu-repo/semantics/article | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
dc.type.version | info:eu-repo/semantics/publishedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Estadística e Investigación Operativa | es |
dc.relation.publisherversion | http://doi.org/10.1016/j.cor.2020.105050 | es |
dc.identifier.doi | 10.1016/j.cor.2020.105050 | es |
dc.contributor.group | Universidad de Sevilla. FQM329: Optimización | es |
dc.journaltitle | Computers & Operations Research | es |
dc.publication.volumen | 123 | es |
dc.publication.initialPage | 105050 - 1 | es |
dc.publication.endPage | 105050 - 24 | es |