Progressive Differential Evolution on Clustering Real World Problems

Vincent Berthier 1, 2
1 TAO - Machine Learning and Optimisation
LRI - Laboratoire de Recherche en Informatique, UP11 - Université Paris-Sud - Paris 11, Inria Saclay - Ile de France, CNRS - Centre National de la Recherche Scientifique : UMR8623
Abstract : In this paper, we assess the performances of Differential Evolution on real-world clustering problems. To improve our results, we introduce Progressive Differential Evolution, a small modification of Differential Evolution which aims at optimizing a small number of parameters (eg. one cluster) at the beginning, and incrementally increase the number of optimized parameters.
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Submitted on : Thursday, October 15, 2015 - 7:07:57 AM
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Vincent Berthier. Progressive Differential Evolution on Clustering Real World Problems. Artifical Evolution 2015, Oct 2015, Lyon, France. ⟨hal-01215803⟩

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