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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