Validating clusters using the Hopkins statistic

  title={Validating clusters using the Hopkins statistic},
  author={A. Banerjee and R. Dav{\'e}},
  journal={2004 IEEE International Conference on Fuzzy Systems (IEEE Cat. No.04CH37542)},
  pages={149-153 vol.1}
  • A. Banerjee, R. Davé
  • Published 2004
  • Mathematics, Computer Science
  • 2004 IEEE International Conference on Fuzzy Systems (IEEE Cat. No.04CH37542)
  • A novel scheme for cluster validity using a test for random position hypothesis is proposed. The random position hypothesis is tested against an alternative clustered hypothesis on every cluster produced by a partitioning algorithm. A test statistic such as the well-known Hopkins statistic could be used as a basis to accept or reject the random position hypothesis, which is also the null hypothesis in this case. The Hopkins statistic is known to be a fair estimator of randomness in a data set… CONTINUE READING
    101 Citations

    Figures and Topics from this paper

    A recursive clustering methodology using a genetic algorithm
    • A. Banerjee, S. Louis
    • Mathematics, Computer Science
    • 2007 IEEE Congress on Evolutionary Computation
    • 2007
    • 12
    • PDF
    A Hybrid Heuristic with Hopkins Statistic for the Automatic Clustering Problem
    • 1
    • Highly Influenced
    An improved genetic algorithm for robust fuzzy clustering with unknown number of clusters
    • A. Banerjee
    • Mathematics
    • 2010 Annual Meeting of the North American Fuzzy Information Processing Society
    • 2010
    • 7
    A context-sensitive crossover operator for clustering applications
    • A. Banerjee, R. Davé
    • Mathematics, Computer Science
    • IEEE Congress on Evolutionary Computation
    • 2010
    • 2
    Giving Fuzziness to Spatial Clusters: a New Index for Choosing the Optimal Number of Clusters
    • 3
    To Cluster, or Not to Cluster: An Analysis of Clusterability Methods
    • 46
    • PDF
    A Comprehensive Comparison of Different Clustering Methods for Reliability Analysis of Microarray Data
    • 4
    • PDF
    To Cluster, or Not to Cluster: How to Answer theestion
    • 1
    • PDF


    A test for multidimensional clustering tendency
    • 37
    Tests of randomness based on distance methods
    • 49
    A Validity Measure for Fuzzy Clustering
    • X. Xie, G. Beni
    • Mathematics, Computer Science
    • IEEE Trans. Pattern Anal. Mach. Intell.
    • 1991
    • 2,963
    Visual cluster validity (VCV) displays for prototype generator clustering methods
    • J. Bezdek, R. Hathaway
    • Mathematics, Computer Science
    • The 12th IEEE International Conference on Fuzzy Systems, 2003. FUZZ '03.
    • 2003
    • 10
    Cluster Validity for the Fuzzy c-Means Clustering Algorithrm
    • M. P. Windham
    • Mathematics, Medicine
    • IEEE Transactions on Pattern Analysis and Machine Intelligence
    • 1982
    • 212
    Validating fuzzy partitions obtained through c-shells clustering
    • R. Davé
    • Mathematics, Computer Science
    • Pattern Recognit. Lett.
    • 1996
    • 232