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Visualization of High-Dimensional Data by Pairwise Fusion Matrices Using t-SNE

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dc.contributor.authorHusnain, Mujtaba
dc.contributor.authorMissen, Malik
dc.contributor.authorMumtaz, Shahzad
dc.contributor.authorLuqman, Muhammad
dc.contributor.authorCoustaty, Mickaël
dc.contributor.authorOgier, Jean-Marc
dc.date.accessioned2024-04-09T15:39:02Z
dc.date.available2024-04-09T15:39:02Z
dc.date.issued2019-01-17
dc.descriptionThis research was co-funded by HEC Pakistan in collaboration with CampusFrance, France. PERIDOT is the Franco-Pakistani Hubert Curien Partnership (PHC) Program providing opportunities to Pakistani and French researchers to interact for joint research activities. Check the details at http//www.hec.gov.pk/english/services/faculty/peridot/Pages/default.aspx. The Région Nouvelle-Aquitaine and and the European Union have partially funded this work in the framework of the project P-2017-BAFE-46.en
dc.description.statusPeer revieweden
dc.format.extent16
dc.format.extent1738104
dc.identifier281561931
dc.identifierc06d169c-f5a7-40a6-a3eb-fc06e8c9c9f9
dc.identifier85061147082
dc.identifier.citationHusnain, M, Missen, M, Mumtaz, S, Luqman, M, Coustaty, M & Ogier, J-M 2019, 'Visualization of High-Dimensional Data by Pairwise Fusion Matrices Using t-SNE', Symmetry, vol. 11, no. 1, 107. https://doi.org/10.3390/sym11010107en
dc.identifier.doi10.3390/sym11010107
dc.identifier.iss1en
dc.identifier.issn2073-8994
dc.identifier.othercrossref: 10.3390/sym11010107
dc.identifier.otherORCID: /0000-0003-2606-2405/work/144004009
dc.identifier.urihttps://hdl.handle.net/2164/23199
dc.identifier.urlhttp://www.mdpi.com/2073-8994/11/1/107en
dc.identifier.vol11en
dc.language.isoeng
dc.relation.ispartofSymmetryen
dc.subjectdimension reductionen
dc.subjectmultidimensional information visualizationen
dc.subjectEuclidean distanceen
dc.subjectembedding algorithmsen
dc.subjectpattern classificationen
dc.subjectQA75 Electronic computers. Computer scienceen
dc.subject.lccQA75en
dc.titleVisualization of High-Dimensional Data by Pairwise Fusion Matrices Using t-SNEen
dc.typeJournal articleen

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