Feature Selection Using Counting Grids: Application to Microarray Data

  • Pietro Lovato
  • Manuele Bicego
  • Marco Cristani
  • Nebojsa Jojic
  • Alessandro Perina
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7626)


In this paper a novel feature selection scheme is proposed, which exploits the potentialities of a recent probabilistic generative model, the Counting Grid. This model is able to cluster together similar observations, highlighting the compactness of a class and its underlying structure. The proposed feature selection scheme is applied to the expression microarray scenario, a peculiar context with very few patterns and a huge number of features. Experiments on benchmark datasets show that the proposed approach is effective and stable, assessing state-of-the-art classification accuracies.


feature selection gene selection generative models 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Pietro Lovato
    • 1
  • Manuele Bicego
    • 1
  • Marco Cristani
    • 1
  • Nebojsa Jojic
    • 2
  • Alessandro Perina
    • 2
  1. 1.Computer Science DepartmentUniversity of VeronaItaly
  2. 2.Microsoft ResearchUSA

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