Hybrid differential evolution algorithm for optimal clustering

@article{Tvrdk2015HybridDE,
  title={Hybrid differential evolution algorithm for optimal clustering},
  author={Josef Tvrd{\'i}k and Ivan Kriv{\'y}},
  journal={Appl. Soft Comput.},
  year={2015},
  volume={35},
  pages={502-512}
}
Abstract: The problem of optimal non-hierarchical clustering is addressed. A new algorithm combining differential evolution and k-means is proposed and tested on eight well-known realworld data sets. The classification of objects to be optimized is encoded by the cluster centres in differential evolution (DE) algorithm. A new efficient heuristic for this rearrangement was also proposed. The plain DE variants with and without the rearrangement were compared with corresponding hybrid k-means… CONTINUE READING