HAWKS: Evolving Challenging Benchmark Sets for Cluster Analysis

  title={HAWKS: Evolving Challenging Benchmark Sets for Cluster Analysis},
  author={Cameron Shand and Richard W. Allmendinger and Julia Handl and Andrew M. Webb and John A. Keane},
—Comprehensive benchmarking of clustering algo- rithms is rendered difficult by two key factors: (i) the elusiveness of a unique mathematical definition of this unsupervised learning approach and (ii) dependencies between the generating models or clustering criteria adopted by some clustering algorithms and indices for internal cluster validation. Consequently, there is no consensus regarding the best practice for rigorous benchmarking, and whether this is possible at all outside the context of a… 

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