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dc.creatorChavarría Molina, Jeffry
dc.creatorFallas Monge, Juan José
dc.creatorTrejos Zelaya, Javier
dc.date.accessioned2021-10-31T17:19:05Z
dc.date.available2021-10-31T17:19:05Z
dc.date.issued2020-04-18
dc.identifier.citationhttps://link.springer.com/chapter/10.1007%2F978-981-15-2700-5_16
dc.identifier.isbn978-981-15-2700-5
dc.identifier.issn2524-4027
dc.identifier.urihttps://hdl.handle.net/10669/84940
dc.description.abstractAn ant colony optimization approach for partitioning a set of objects is proposed. In order to minimize the intra-variance, or within sum-of-squares, of the partitioned classes, we construct ant-like solutions by a constructive approach that selects objects to be put in a class with a probability that depends on the distance between the object and the centroid of the class (visibility) and the pheromone trail; the latter depends on the class memberships that have been defined along the iterations. The procedure is improved with the application of K-means algorithm in some iterations of the ant colony method. We performed a simulation study in order to evaluate the method with a Monte Carlo experiment that controls some sensitive parameters of the clustering problem. After some tuning of the parameters, the method has also been applied to some benchmark real-data sets. Encouraging results were obtained in nearly all cases.es_ES
dc.description.sponsorshipInstituto Tecnológico de Costa Rica/[5402-1440-3901]/TEC/Costa Ricaes_ES
dc.description.sponsorshipUniversidad de Costa Rica/[821-B1-122]/UCR/Costa Ricaes_ES
dc.language.isoenges_ES
dc.sourceAdvanced Studies in Behaviormetrics and Data Science (pp.265-282).Singapore: Springer Nature Singaporees_ES
dc.subjectClusteringes_ES
dc.subjectAnt colony optimizationes_ES
dc.subjectCombinatorial optimizationes_ES
dc.subjectWithin-class inertiaes_ES
dc.titleClustering via ant colonies: Parameter analysis and improvement of the algorithmes_ES
dc.typecapítulo de libro
dc.identifier.doi10.1007/978-981-15-2700-5_16
dc.description.procedenceUCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias Básicas::Centro de Investigaciones en Matemáticas Puras y Aplicadas (CIMPA)es_ES
dc.description.procedenceUCR::Vicerrectoría de Docencia::Ciencias Básicas::Facultad de Ciencias::Escuela de Matemáticaes_ES
dc.identifier.codproyecto821-B1-122


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