Publication:
Classification Model for Data Streams Based on Similarity

Simple item page
dc.contributor.authorMena Torres, Dayrelis
dc.contributor.authorAguilar-Ruiz, Jesús Salvador
dc.contributor.authorRodríguez- Sarabia, Yanet
dc.date.accessioned2026-03-02T11:08:13Z
dc.date.available2026-03-02T11:08:13Z
dc.date.issued2011-07-01
dc.description.abstractMining data streams is a field of study that poses new challenges. This research delves into the study of applying different techniques of classification of data streams, and carries out a comparative analysis with a proposal based on similarity; introducing a new form of management of representative data models and policies of insertion and removal, advancing also in the design of appropriate estimators to improve classification performance and updating of the model.
dc.description.sponsorshipDeporte e Informática
dc.format.mimetypeapplication/pdf
dc.identifier.citationMena Torres, D., Aguilar Ruiz, J., Rodríguez Sarabia, Y. (2011). Classification Model for Data Streams Based on Similarity. In: Mehrotra, K.G., Mohan, C.K., Oh, J.C., Varshney, P.K., Ali, M. (eds) Modern Approaches in Applied Intelligence. IEA/AIE 2011. Lecture Notes in Computer Science(), vol 6703. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21822-4_1
dc.identifier.doi10.1007/978-3-642-21822-4_1
dc.identifier.urihttps://hdl.handle.net/10433/26333
dc.language.isoen
dc.publisherSpringer
dc.rights.accessRightsrestricted access
dc.subjectData streams,Classification,Similarity
dc.titleClassification Model for Data Streams Based on Similarity
dc.typejournal article
dc.type.hasVersionVoR
dspace.entity.typePublication
relation.isAuthorOfPublication5d0a50b3-624e-4b73-914e-0464ccd668dc
relation.isAuthorOfPublication5ca8a962-86a4-4465-aad6-508a8e70adc7
relation.isAuthorOfPublication.latestForDiscovery5d0a50b3-624e-4b73-914e-0464ccd668dc

Files

Original bundle

Now showing 1 - 1 of 1
Thumbnail Image
Name:
978-3-642-21822-4_art.pdf
Size:
4.01 MB
Format:
Adobe Portable Document Format
Download

Collections

DDI - Comunicaciones de congresos