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An Approach to Variable Aggregation in Efficiency Analysis

dc.contributor.authorNoncheva, Veska
dc.contributor.authorMendes, Armando B.
dc.contributor.authorSilva, Emiliana
dc.date.accessioned2013-07-19T16:47:59Z
dc.date.available2013-07-19T16:47:59Z
dc.date.issued2009
dc.date.updated2013-07-17T15:18:32Z
dc.descriptionConference: The paper is selected from International Conference "Classification, Forecasting, Data Mining" CFDM 2009, Varna, Bulgaria, June-July 2009.en
dc.description.abstractIn the nonparametric framework of Data Envelopment Analysis the statistical properties of its estimators have been investigated and only asymptotic results are available. For DEA estimators results of practical use have been proved only for the case of one input and one output. However, in the real world problems the production process is usually well described by many variables. In this paper a machine learning approach to variable aggregation based on Canonical Correlation Analysis is presented. This approach is applied for efficiency estimation of all the farms in Terceira Island of the Azorean archipelago.en
dc.identifier.citationNoncheva, Veska; Mendes, Armando Brito; Silva, Emiliana. "An Approach to Variable Aggregation in Efficiency Analysis". «International Book Series 'Information Science and Computing' : Classification, Forecasting, Data Mining», Book 8, (Supplement to the International Journal "Information Technologies & Knowledge", Volume 3): 97-104, 2009. http://hdl.handle.net/10525/1195.en
dc.identifier.issn1313-0455 (Print)
dc.identifier.issn1313-048X (Online)
dc.identifier.urihttp://hdl.handle.net/10400.3/2144
dc.language.isoengpor
dc.peerreviewedyespor
dc.publisherInstitute of Information Theories and Applications FOI ITHEAen
dc.relation.publisherversionhttp://hdl.handle.net/10525/1195por
dc.subjectCanonical Correlation Analysisen
dc.subjectData Envelopment Analysisen
dc.subjectEfficiencyen
dc.subjectVariable Aggregationen
dc.subjectMultivariate Statisticsen
dc.subjectData Miningen
dc.titleAn Approach to Variable Aggregation in Efficiency Analysisen
dc.typejournal article
dspace.entity.typePublication
oaire.citation.conferencePlaceSofia, Bulgariaen
oaire.citation.endPage104por
oaire.citation.startPage97por
oaire.citation.titleInternational Book Series "Information Science and Computing"en
oaire.citation.volumeBook 8por
rcaap.rightsopenAccesspor
rcaap.typearticlepor

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