Progressive Differential Evolution on Clustering Real World Problems
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.
Domains
Numerical Analysis [cs.NA]
Origin : Files produced by the author(s)
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