A Redundancy Study for Feature Selection in Biological Data

  • Emna Mouelhi
  • Waad Bouaguel
  • Ghazi Bel Mufti
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9468)


The curse of dimensionality is one of the well known issues in Biological data bases. A possible solution to avoid this issue is to use feature selection approach. Filter feature selection are well know feature selection methods that selects the most significant features and discards the rest according to their significance level. In general The set of eliminated features may hide some useful information that may be valuable in further studies. Hence, this paper present a new approach for filter feature selection that uses redundant features to create new instances and avoid the curse of dimensionality.


Curse of dimensionality Relief Feature selection Filter 


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.ISGUniversity of TunisTunisTunisia
  2. 2.LARODEC, ISGUniversity of TunisTunisTunisia
  3. 3.LARIME, ESSECUniversity of TunisTunisTunisia

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