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Large scale anomaly detection in mixed numerical and categorical input spaces

dc.contributor.authorEiras Franco, C.
dc.contributor.authorMartínez Rego, D.
dc.contributor.authorGuijarro Berdiñas, B.
dc.contributor.authorAlonso Betanzos, A.
dc.contributor.authorBahamonde Rionda, Antonio 
dc.date.accessioned2019-08-21T07:34:06Z
dc.date.available2019-08-21T07:34:06Z
dc.date.issued2019
dc.identifier.citationInformation Sciences, 487, p. 115-127 (2019); doi:10.1016/j.ins.2019.03.013
dc.identifier.issn0020-0255
dc.identifier.urihttp://hdl.handle.net/10651/52224
dc.description.sponsorshipThis research has been financially supported in part by the Spanish Ministerio de Economía y Competitividad (research projects TIN 2015-65069-C2, both 1-R and 2-R), by the Xunta de Galicia (Grants GRC2014/035 and ED431G/01) and the European Union Regional Development Funds.
dc.format.extentp. 115-127
dc.language.isoeng
dc.relation.ispartofInformation Sciences, 487
dc.rights© 2019 Elsevier
dc.sourceScopus
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85062506396&doi=10.1016%2fj.ins.2019.03.013&partnerID=40&md5=c302ab4e2fdf6e5abbeedae2eed416da
dc.titleLarge scale anomaly detection in mixed numerical and categorical input spaces
dc.typejournal article
dc.identifier.doi10.1016/j.ins.2019.03.013
dc.relation.projectIDMINECO/TIN 2015-65069-C2
dc.relation.publisherversionhttp://dx.doi.org/10.1016/j.ins.2019.03.013
dc.rights.accessRightsopen access
dc.type.hasVersionAM


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