Iterative shrinking method for clustering problems

@article{Frnti2006IterativeSM,
  title={Iterative shrinking method for clustering problems},
  author={Pasi Fr{\"a}nti and Olli Virmajoki},
  journal={Pattern Recognition},
  year={2006},
  volume={39},
  pages={761-775}
}
Agglomerative clustering generates the partition hierarchically by a sequence of merge operations. We propose an alternative to the merge-based approach by removing the clusters iteratively one by one until the desired number of clusters is reached. We apply local optimization strategy by always removing the cluster that increases the distortion the least. Data structures and their update strategies are considered. The proposed algorithm is applied as a crossover method in a genetic algorithm… CONTINUE READING

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