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dc.contributor.authorC-Rella, Jorge
dc.date.accessioned2024-07-15T14:20:05Z
dc.date.available2024-07-15T14:20:05Z
dc.date.issued2024
dc.identifier.citationJorge, C. (2024). CABRA: Clustering algorithm based on regular arrangement. Operations Research Letters, 107137. https://doi.org/10.1016/j.orl.2024.107137es_ES
dc.identifier.issn0167-6377 (print)
dc.identifier.issn1872-7468 (electronic)
dc.identifier.urihttp://hdl.handle.net/2183/38006
dc.description.abstract[Abstract]: Clustering is an unsupervised learning technique for organizing complex datasets into coherent groups. A novel clustering algorithm is presented, with a simple grouping concept depending on only one hyperparameter, which makes it suitable for further extensions to any topology and space. It is compared to state-of-the-art algorithms, overall achieving a better performance independently on the structure and complexity of the data, making the proposed algorithm a valuable tool for real applications such as market segmentation, sentiment analysis and anomaly detection.es_ES
dc.description.sponsorshipThis research has been financed by the Grant PID2020-113578RB-I00, funded by MCIN/AEI/10.2039/501100011033/. It has also been supported by the Xunta de Galicia (Grupos de Referencia Competitiva ED431C-2020/14) and by CITIC that is supported by Xunta de Galicia, convenio de colaboración entre la Consellería de Cultura, Educación, Formación Profesional e Universidades y las universidades gallegas para el refuerzo de los centros de investigación del Sistema Universitario de Galicia (CIGUS). The first author was financed by the Axencia Galega de Innovación Industrial PhD Grant 14-IN606D-2021-2607768.es_ES
dc.description.sponsorshipXunta de Galicia; ED431C-2020/14es_ES
dc.description.sponsorshipXunta de Galicia; 14-IN606D-2021-2607768es_ES
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.relationinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-113578RB-I00/ES/METODOS ESTADISTICOS FLEXIBLES EN CIENCIA DE DATOS PARA DATOS COMPLEJOS Y DE GRAN VOLUMEN: TEORIA Y APLICACIONESes_ES
dc.relation.urihttps://doi.org/10.1016/j.orl.2024.107137es_ES
dc.rightsAtribución 4.0 Internacional (CC-BY)es_ES
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.subjectClusteringes_ES
dc.subjectSegmentationes_ES
dc.subjectClassificationes_ES
dc.subjectOutlier detectiones_ES
dc.titleCABRA: Clustering algorithm based on regular arrangementes_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessinfo:eu-repo/semantics/openAccesses_ES
UDC.journalTitleOperations Research Letterses_ES
UDC.volume55es_ES
UDC.issue107137es_ES
UDC.startPage1es_ES
UDC.endPage7es_ES
dc.identifier.doi10.1016/j.orl.2024.107137


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