An Evolutionary Approach to Multiobjective Clustering

@article{Handl2007AnEA,
  title={An Evolutionary Approach to Multiobjective Clustering},
  author={Julia Handl and Joshua D. Knowles},
  journal={IEEE Transactions on Evolutionary Computation},
  year={2007},
  volume={11},
  pages={56-76}
}
The framework of multiobjective optimization is used to tackle the unsupervised learning problem, data clustering, following a formulation first proposed in the statistics literature. The conceptual advantages of the multiobjective formulation are discussed and an evolutionary approach to the problem is developed. The resulting algorithm, multiobjective clustering with automatic k-determination, is compared with a number of well-established single-objective clustering algorithms, a modern… CONTINUE READING
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