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Conference Paper: Improving classification accuracy in high dimensional data: A Four-step approach

TitleImproving classification accuracy in high dimensional data: A Four-step approach
Authors
Issue Date2019
PublisherNational Council on Measurement in Education.
Citation
National Council on Measurement in Education 2019 NCME Annual Meeting & Training Sessions: Communicating with the Public about Educational Measurement, Toronto, ON, Canada, 4-8 April 2019 How to Cite?
AbstractIn this study, covariates are incorporated to improve classification accuracy in large dimensional cognitive diagnostic tests. The performance of the proposed approach was examined in a simulation study. Results showed that the proposed approach could increase information obtained from CDM and improve the classification accuracy when tests are not informative.
DescriptionPaper Session: Advances in Cognitive Diagnostic Modeling
Persistent Identifierhttp://hdl.handle.net/10722/274479

 

DC FieldValueLanguage
dc.contributor.authorSun, Y-
dc.contributor.authorde la Torre, J-
dc.date.accessioned2019-08-18T15:02:31Z-
dc.date.available2019-08-18T15:02:31Z-
dc.date.issued2019-
dc.identifier.citationNational Council on Measurement in Education 2019 NCME Annual Meeting & Training Sessions: Communicating with the Public about Educational Measurement, Toronto, ON, Canada, 4-8 April 2019-
dc.identifier.urihttp://hdl.handle.net/10722/274479-
dc.descriptionPaper Session: Advances in Cognitive Diagnostic Modeling-
dc.description.abstractIn this study, covariates are incorporated to improve classification accuracy in large dimensional cognitive diagnostic tests. The performance of the proposed approach was examined in a simulation study. Results showed that the proposed approach could increase information obtained from CDM and improve the classification accuracy when tests are not informative.-
dc.languageeng-
dc.publisherNational Council on Measurement in Education. -
dc.relation.ispartofNational Council on Measurement in Education (NCME) 2019 Annual Meeting & Training Sessions-
dc.titleImproving classification accuracy in high dimensional data: A Four-step approach-
dc.typeConference_Paper-
dc.identifier.emailde la Torre, J: jdltorre@hku.hk-
dc.identifier.authorityde la Torre, J=rp02159-
dc.identifier.hkuros302330-

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