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Merged Tree-CAT: A fast method for building precise computerized adaptive tests based on decision trees

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dc.affiliation.dptoUC3M. Departamento de Estadísticaes
dc.contributor.authorRodriguez Cuadrado, Javier
dc.contributor.authorDelgado Gómez, David
dc.contributor.authorLaria de la Cruz, Juan Carlos
dc.contributor.authorRodriguez-Cuadrado, Sara
dc.contributor.funderMinisterio de Economía y Competitividad (España)es
dc.date.accessioned2021-06-24T10:50:06Z
dc.date.available2022-04-01T23:00:05Z
dc.date.issued2020-04-01
dc.description.abstractOver the last few years, there has been an increasing interest in the creation of Computerized Adaptive Tests (CATs) based on Decision Trees (DTs). Among the available methods, the Tree-CAT method has been able to demonstrate a mathematical equivalence between both techniques. However, this method has the inconvenience of requiring a high performance cluster while taking a few days to perform its computations. This article presents the Merged Tree-CAT method, which extends the Tree-CAT technique, to create CATs based on DTs in just a few seconds in a personal computer. In order to do so, the Merged Tree-CAT method controls the growth of the tree by merging those branches in which both the distribution and the estimation of the latent level are similar. The performed experiments show that the proposed method obtains estimations of the latent level which are comparable to the obtained by the state-of-the-art techniques, while drastically reducing the computational time.en
dc.description.sponsorshipNumerical experiments were conducted in Uranus, a supercomputer cluster located at Universidad Carlos III de Madrid and jointly funded by EU-FEDER funds and by the Spanish Government via the National Projects nos. UNC313-4E-2361, ENE2009-12213- C03-03, ENE2012-33219, ENE2012-31753 and ENE2015-68265-P. This article was also funded by the Spanish National Project no. RTI2018-101857-B-I00.en
dc.format.extent7
dc.identifier.bibliographicCitationRodríguez-Cuadrado, J., Delgado-Gómez, D., Laria, J. C. & Rodríguez-Cuadrado, S. (2020). Merged Tree-CAT: A fast method for building precise computerized adaptive tests based on decision trees. Expert Systems with Applications, 143, 113066.en
dc.identifier.doihttps://dx.doi.org/10.1016/j.eswa.2019.113066
dc.identifier.issn0957-4174
dc.identifier.publicationfirstpage1
dc.identifier.publicationissue113066
dc.identifier.publicationlastpage7
dc.identifier.publicationtitleExpert Systems with Applicationsen
dc.identifier.publicationvolume143
dc.identifier.urihttps://hdl.handle.net/10016/32929
dc.identifier.uxxiAR/0000025689
dc.language.isoeng
dc.publisherElsevieren
dc.relation.projectIDGobierno de España. ENE2009-12213-C03-03es
dc.relation.projectIDGobierno de España. ENE2012-33219es
dc.relation.projectIDGobierno de España. ENE2012-31753es
dc.relation.projectIDGobierno de España. UNC313-4E-2361es
dc.relation.projectIDGobierno de España. ENE2015-68265-Pes
dc.relation.projectIDGobierno de España. RTI2018-101857-B-I00es
dc.rights© 2019 Elsevier Ltd.en
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España*
dc.rights.accessRightsopen accessen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.subject.ecienciaEstadísticaes
dc.subject.otherComputerized adaptive testsen
dc.subject.otherDecision treesen
dc.subject.otherLinear programmingen
dc.titleMerged Tree-CAT: A fast method for building precise computerized adaptive tests based on decision treesen
dc.typeresearch article*
dc.type.hasVersionAM*
dspace.entity.typePublication
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