Título: Proposta e Análise de um Algoritmo Evolutivo Construtivo para o Problema de Clusterização Automática
Autores: Soares, Stênio Sã Furtado; Ochi, Luiz Satoru
Resumo: Clustering, also known as unsupervised classification, is a process by which a data set is partitioned into different clusters such that objects of the same cluster are as similar as possible and objects of different clusters are as dissimilar as possible. In clustering algorithms, it is usually assumed that the number of clusters is known or given. Unfortunately, the optimal number of clusters is unknown for many application of this problem. These problems are known as Automatic Clustering Problems (ACP). This paper presents an Efficient Constructive Evolutionary Algorithm to solve the ACP. Extensive computational experiments show that the proposed algorithm outperforms a genetic algorithm from the literature, improving both, the solution quality and the computational time required.
Palavras-chave: Algoritmos Evolutivos; Problemas de Clusterização Automática
Código DOI: 10.21528/CBRN2005-061
Artigo em PDF: CBRN2005_061.pdf
Arquivo BibTex: CBRN2005_061.bib