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Book Chapter: Improving Attribute Classification Accuracy In High Dimensional Data: A Four-step Latent Regression Approach

TitleImproving Attribute Classification Accuracy In High Dimensional Data: A Four-step Latent Regression Approach
Authors
Issue Date2020
PublisherInformation Age Publishing
Citation
Improving Attribute Classification Accuracy In High Dimensional Data: A Four-step Latent Regression Approach. In H. Jiao & R. W. Lissitz (Eds.) (Eds.), Innovative Psychometric Modeling and Method, p. 17-44. Charlotte, NC: Information Age Publishing, 2020 How to Cite?
Persistent Identifierhttp://hdl.handle.net/10722/289945

 

DC FieldValueLanguage
dc.contributor.authorSun, Y-
dc.contributor.authorde la Torre, J-
dc.date.accessioned2020-10-22T08:19:43Z-
dc.date.available2020-10-22T08:19:43Z-
dc.date.issued2020-
dc.identifier.citationImproving Attribute Classification Accuracy In High Dimensional Data: A Four-step Latent Regression Approach. In H. Jiao & R. W. Lissitz (Eds.) (Eds.), Innovative Psychometric Modeling and Method, p. 17-44. Charlotte, NC: Information Age Publishing, 2020-
dc.identifier.urihttp://hdl.handle.net/10722/289945-
dc.languageeng-
dc.publisherInformation Age Publishing-
dc.relation.ispartofInnovative Psychometric Modeling and Method-
dc.titleImproving Attribute Classification Accuracy In High Dimensional Data: A Four-step Latent Regression Approach-
dc.typeBook_Chapter-
dc.identifier.emailde la Torre, J: j.delatorre@hku.hk-
dc.identifier.authorityde la Torre, J=rp02159-
dc.identifier.hkuros317591-
dc.identifier.spage17-
dc.identifier.epage44-
dc.publisher.placeCharlotte, NC-

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