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}
}
• 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
30 Citations

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