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Clustering via ant colonies: Parameter analysis and improvement of the algorithm
dc.creator | Chavarría Molina, Jeffry | |
dc.creator | Fallas Monge, Juan José | |
dc.creator | Trejos Zelaya, Javier | |
dc.date.accessioned | 2021-10-31T17:19:05Z | |
dc.date.available | 2021-10-31T17:19:05Z | |
dc.date.issued | 2020-04-18 | |
dc.identifier.citation | https://link.springer.com/chapter/10.1007%2F978-981-15-2700-5_16 | |
dc.identifier.isbn | 978-981-15-2700-5 | |
dc.identifier.issn | 2524-4027 | |
dc.identifier.uri | https://hdl.handle.net/10669/84940 | |
dc.description.abstract | An 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.sponsorship | Instituto Tecnológico de Costa Rica/[5402-1440-3901]/TEC/Costa Rica | es_ES |
dc.description.sponsorship | Universidad de Costa Rica/[821-B1-122]/UCR/Costa Rica | es_ES |
dc.language.iso | eng | es_ES |
dc.source | Advanced Studies in Behaviormetrics and Data Science (pp.265-282).Singapore: Springer Nature Singapore | es_ES |
dc.subject | Clustering | es_ES |
dc.subject | Ant colony optimization | es_ES |
dc.subject | Combinatorial optimization | es_ES |
dc.subject | Within-class inertia | es_ES |
dc.title | Clustering via ant colonies: Parameter analysis and improvement of the algorithm | es_ES |
dc.type | capítulo de libro | |
dc.identifier.doi | 10.1007/978-981-15-2700-5_16 | |
dc.description.procedence | UCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias Básicas::Centro de Investigaciones en Matemáticas Puras y Aplicadas (CIMPA) | es_ES |
dc.description.procedence | UCR::Vicerrectoría de Docencia::Ciencias Básicas::Facultad de Ciencias::Escuela de Matemática | es_ES |
dc.identifier.codproyecto | 821-B1-122 |
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