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Colanzi, T E; Assunção, W K G; Pozo, A T R; Vendramin, A C B K; Pereira, D A B
2010 XXIX International Conference of the Chilean Computer Science Society, 2010-Nov.Conference Proceeding
Cluster analysis is used in several research areas to classify data sets in groups by their similar characteristics. Metaheuristic-based techniques, such as Genetic Algorithms (GAs) and Ant Colony Optimization (ACO), have been applied in order to increase the clustering algorithm performance. GA and ACO-based clustering algorithms are capable of efficiently and automatically forming natural groups from a pre-defined number of clusters. This paper presents a GA and an ACO algorithm to the clustering problem. Both algorithms were refined using local search in order to improve the clustering accuracy. The results are compared on numeric UCI databases.
