A comparative study of machine learning methods for ordinal classification with absolute and relative information

dc.contributor.author	Tang, Mengzi
dc.contributor.author	Pérez Fernández, Raúl
dc.contributor.author	De Baets, Bernard
dc.date.accessioned	2022-04-22T11:14:04Z
dc.date.available	2022-04-22T11:14:04Z
dc.date.issued	2021
dc.identifier.citation	Knowledge-based systems, 230, (2021); doi:10.1016/j.knosys.2021.107358
dc.identifier.issn	0950-7051
dc.identifier.issn	1872-7409
dc.identifier.uri	http://hdl.handle.net/10651/62927
dc.description.sponsorship	China Scholarship Council (CSC)China Scholarship Council; KER-MIT, Department of Data Analysis and Mathematical Modelling, Ghent University, Belgium; Research Foundation of Flanders, Belgium [FWO17/PDO/160]; Spanish MINECOSpanish Government [TIN-2017-87600-P]; Flemish Government, Belgium
dc.language.iso	eng
dc.relation.ispartof	Knowledge-based systems
dc.rights	© 2021 Elsevier B. V.
dc.rights	CC Reconocimiento - No comercial - Sin obra derivada 4.0 Internacional
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.source	WOS:000697004300010
dc.title	A comparative study of machine learning methods for ordinal classification with absolute and relative information
dc.type	journal article
dc.identifier.doi	10.1016/j.knosys.2021.107358
dc.relation.projectID	TIN-2017-87600-P
dc.relation.publisherversion	http://dx.doi.org/10.1016/j.knosys.2021.107358
dc.rights.accessRights	open access
dc.type.hasVersion	AM

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