Statistically Significant Discriminative Patterns Searching

  • Hoang Son PhamEmail author
  • Gwendal Virlet
  • Dominique Lavenier
  • Alexandre Termier
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11708)


In this paper, we propose a novel algorithm, named SSDPS, to discover patterns in two-class datasets. The SSDPS algorithm owes its efficiency to an original enumeration strategy of the patterns, which allows to exploit some degrees of anti-monotonicity on the measures of discriminance and statistical significance. Experimental results demonstrate that the performance of the SSDPS algorithm is better than others. In addition, the number of generated patterns is much less than the number of the other algorithms. Experiment on real data also shows that SSDPS efficiently detects multiple SNPs combinations in genetic data.


Discriminative patterns Discriminative measures Statistical significance Anti-monotonicity 


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Hoang Son Pham
    • 1
    Email author
  • Gwendal Virlet
    • 2
  • Dominique Lavenier
    • 2
  • Alexandre Termier
    • 2
  1. 1.ICTEAMUCLouvainLouvain-la-NeuveBelgium
  2. 2.Univ Rennes, Inria, CNRS, IRISARennesFrance

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