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CIMCA
2005
IEEE

A New Evolutionary Algorithm for Determining the Optimal Number of Clusters

13 years 9 months ago
A New Evolutionary Algorithm for Determining the Optimal Number of Clusters
Estimating the optimal number of clusters for a dataset is one of the most essential issues in cluster analysis. An improper pre-selection for the number of clusters might easily lead to bad clustering outcome. In this paper, we propose a new evolutionary algorithm to address this issue. Specifically, the proposed evolutionary algorithm defines a new entropy-based fitness function, and three new genetic operators for splitting, merging, and removing clusters. Empirical evaluations using the synthetic dataset and an existing benchmark show that the proposed evolutionary algorithm can exactly estimate the optimal number of clusters for a set of data.
Wei Lu, Issa Traoré
Added 24 Jun 2010
Updated 24 Jun 2010
Type Conference
Year 2005
Where CIMCA
Authors Wei Lu, Issa Traoré
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