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Feature Construction and δ-Free Sets in 0/1 Samples

  • Nazha Selmaoui
  • Claire Leschi
  • Dominique Gay
  • Jean-François Boulicaut
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4265)

Abstract

Given the recent breakthrough in constraint-based mining of local patterns, we decided to investigate its impact on feature construction for classification tasks. We discuss preliminary results concerning the use of the so-called δ-free sets. Our guess is that their minimality might help to collect important features. Once these sets are computed, we propose to select the essential ones w.r.t. class separation and generalization as new features. Our experiments have given encouraging results.

Keywords

Frequent Itemset Class Separation Feature Construction Interestingness Measure Viral Meningitis 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Nazha Selmaoui
    • 1
  • Claire Leschi
    • 2
  • Dominique Gay
    • 1
  • Jean-François Boulicaut
    • 2
  1. 1.ERIMUniversity of New Caledonia 
  2. 2.INSA Lyon, LIRIS CNRS UMR 5205 

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