Clustering Oligarchies

  title={Clustering Oligarchies},
  author={Margareta Ackerman and Shai Ben-David and David Loker and Sivan Sabato},
We investigate the extent to which clustering algorithms are robust to the addition of a small, potentially adversarial, set of points. Our analysis reveals radical differences in the robustness of popular clustering methods. k-means and several related techniques are robust when data is clusterable, and we provide a quantitative analysis capturing the precise relationship between clusterability and robustness. In contrast, common linkage-based algorithms and several standard objective-function… CONTINUE READING
11 Citations
14 References
Similar Papers


Publications referenced by this paper.
Showing 1-10 of 14 references

A review of robust clustering methods

  • L. A. Garćıa-Escudero, A. Gordaliza, C. Matrán, A. Mayo-Iscar
  • Advances in Data Analysis and Classification,
  • 2010
Highly Influential
5 Excerpts

A robust method for cluster analysis

  • M. T. Gallegos, G. Ritter
  • The Annals of Statistics,
  • 2005
1 Excerpt

Robustness properties of k means and trimmed k means

  • L. A. Garcia-Escudero, A. Gordaliza
  • Journal of the American Statistical Association,
  • 1999
1 Excerpt

Similar Papers

Loading similar papers…