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Interactive Dimensionality Reduction for Visual Analytics

dc.contributor.authorDíaz Blanco, Ignacio 
dc.contributor.authorCuadrado Vega, Abel Alberto 
dc.contributor.authorPérez López, Daniel 
dc.contributor.authorGarcía Fernández, Francisco Javier 
dc.contributor.authorVerleysen, Michel
dc.date.accessioned2015-12-10T08:48:11Z
dc.date.available2015-12-10T08:48:11Z
dc.date.issued2014
dc.identifier.isbn978-287419095-7
dc.identifier.urihttp://hdl.handle.net/10651/33986
dc.descriptionESANN 2014 proceedings, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (22. 2014. Bruges (Belgium))eng
dc.description.abstractIn this work, we present a novel approach for data visualiza- tion based on interactive dimensionality reduction (iDR). The main idea of the paper relies on considering for visualization the intermediate results of non-convex DR algorithms under changes on the metric of the input data space driven by the user. With an appropriate visualization interface, our approach allows the user to focus on the relationships among dynamically selected groups of variables, as well as to assess the impact of a single variable or groups of variables in the structure of the data.eng
dc.description.sponsorshipFnancial support from the Spanish Ministry of Economy (MINECO) and FEDER funds from the EUeng
dc.format.extentp. 183-188spa
dc.language.isoengspa
dc.publisherESANNspa
dc.relation.ispartofESANN 2014, 22nd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, Bruges, April, 23, 24, 25, 2014: proceedingseng
dc.rightsCC Reconocimiento - No comercial - Sin obras derivadas 4.0 Internacional
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectData visualizationeng
dc.subjectDimensionality reductioneng
dc.subjectMachine learningspa
dc.titleInteractive Dimensionality Reduction for Visual Analyticseng
dc.typeinfo:eu-repo/semantics/bookPartspa
dc.type.dcmitextspa
dc.relation.projectIDMINECO
dc.relation.projectIDFEDER


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CC Reconocimiento - No comercial - Sin obras derivadas 4.0 Internacional
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