Corpus ID: 1072171

Clustering is difficult only when it does not matter

@article{Daniely2012ClusteringID,
  title={Clustering is difficult only when it does not matter},
  author={Amit Daniely and N. Linial and M. Saks},
  journal={ArXiv},
  year={2012},
  volume={abs/1205.4891}
}
  • Amit Daniely, N. Linial, M. Saks
  • Published 2012
  • Mathematics, Computer Science
  • ArXiv
  • Numerous papers ask how difficult it is to cluster data. We suggest that the more relevant and interesting question is how difficult it is to cluster data sets {\em that can be clustered well}. More generally, despite the ubiquity and the great importance of clustering, we still do not have a satisfactory mathematical theory of clustering. In order to properly understand clustering, it is clearly necessary to develop a solid theoretical basis for the area. For example, from the perspective of… CONTINUE READING
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