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Streaming Data Clustering in MOA using the Leader Algorithm
dc.contributor | Belanche Muñoz, Luis Antonio |
dc.contributor.author | Andrés Merino, Jaime |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament de Ciències de la Computació |
dc.date.accessioned | 2015-11-13T13:26:34Z |
dc.date.available | 2015-11-13T13:26:34Z |
dc.date.issued | 2015-10-30 |
dc.identifier.uri | http://hdl.handle.net/2117/79235 |
dc.description.abstract | This 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.iso | eng |
dc.publisher | Universitat Politècnica de Catalunya |
dc.subject | Àrees temàtiques de la UPC::Informàtica |
dc.subject.lcsh | Computer algorithms |
dc.subject.other | StreamLeader |
dc.subject.other | LeaderKernel |
dc.subject.other | stream |
dc.subject.other | clustering |
dc.subject.other | MOA |
dc.subject.other | leader |
dc.subject.other | Hartigan |
dc.subject.other | Clustream |
dc.subject.other | Denstream |
dc.subject.other | Clustree |
dc.subject.other | Network Intrusion |
dc.subject.other | Forest Cover Type |
dc.subject.other | dimensionality |
dc.subject.other | noise |
dc.title | Streaming Data Clustering in MOA using the Leader Algorithm |
dc.type | Master thesis |
dc.subject.lemac | Algorismes computacionals |
dc.identifier.slug | 110659 |
dc.rights.access | Open Access |
dc.date.updated | 2015-11-05T05:00:23Z |
dc.audience.educationlevel | Màster |
dc.audience.mediator | Facultat d'Informàtica de Barcelona |
dc.audience.degree | MÀSTER UNIVERSITARI EN INNOVACIÓ I RECERCA EN INFORMÀTICA (Pla 2012) |