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dc.contributorBelanche Muñoz, Luis Antonio
dc.contributor.authorAndrés Merino, Jaime
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Ciències de la Computació
dc.date.accessioned2015-11-13T13:26:34Z
dc.date.available2015-11-13T13:26:34Z
dc.date.issued2015-10-30
dc.identifier.urihttp://hdl.handle.net/2117/79235
dc.description.abstractThis master thesis presents a novel stream clustering algorithm, called StreamLeader. It presents a way to deliver clustering without the need of resorting to conventional clustering algorithms, like most other algorithms do. We test it, outperforming its state of the art rivals in most of the cases
dc.language.isoeng
dc.publisherUniversitat Politècnica de Catalunya
dc.subjectÀrees temàtiques de la UPC::Informàtica
dc.subject.lcshComputer algorithms
dc.subject.otherStreamLeader
dc.subject.otherLeaderKernel
dc.subject.otherstream
dc.subject.otherclustering
dc.subject.otherMOA
dc.subject.otherleader
dc.subject.otherHartigan
dc.subject.otherClustream
dc.subject.otherDenstream
dc.subject.otherClustree
dc.subject.otherNetwork Intrusion
dc.subject.otherForest Cover Type
dc.subject.otherdimensionality
dc.subject.othernoise
dc.titleStreaming Data Clustering in MOA using the Leader Algorithm
dc.typeMaster thesis
dc.subject.lemacAlgorismes computacionals
dc.identifier.slug110659
dc.rights.accessOpen Access
dc.date.updated2015-11-05T05:00:23Z
dc.audience.educationlevelMàster
dc.audience.mediatorFacultat d'Informàtica de Barcelona


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