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Enhancing Incremental Feature Subset Selection in High-Dimensional Databases by Adding a Backward Step

  • Pablo Bermejo
  • Luis de La Ossa
  • Jose A. Gamez
  • Jose M. Puerta
Conference paper

Abstract

Feature subset selection has become an expensive process due to the relatively recent appearance of high-dimensional databases. Thus, the need has arisen not only for reducing the dimensionality of these datasets, but also for doing it in an efficient way. We propose the design of a new backward search which performs better than other state-of-the-art algorithms in terms of size of the selected subsets and in the number of evaluations, by removing attributes given a smart decremental approach and, besides, it is guided using a heuristic which reduces the needed number of evaluations commonly expected from a backward search.

Notes

Acknowledgments

This work has been partially supported by the JCCM under project PCI08-0048-8577 and CICYT under project TIN2010-20900-C04-03.

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Copyright information

© Springer-Verlag London Limited  2011

Authors and Affiliations

  1. 1.Castilla-La Mancha UniversityAlbaceteSpain

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