@InProceedings{krizek-CAIP-2007,
  IS = { zkontrolovano 13 Dec 2007 },
  UPDATE  = { 2007-10-01 },
  author =      {K{\v r}{\'\i }{\v z}ek, Pavel and
                 Josef Kittler and Hlav{\' a}{\v c}, V{\' a}clav},
  title =       {Improving stability of feature selection methods},
  year =        {2007},
  pages =       {929--936},
  booktitle =   {CAIP 2007: Proceedings of the 12th International
                 Conference on Computer Analysis of Images and
                 Patterns},
  editor =      {Kropatsch, Walter G. and Kampel, Martin and
                 Hanbury, Allan},
  publisher =   {Springer},
  address =     {Berlin, Germany},
  series =      {Lecture Notes in Computer Science},
  isbn =        {978-3-540-74271-5},
  number =      {4673},
  book_pages =  {1007},
  month =       {August},
  day =         {27--29},
  venue =       {Vienna University of Technology, Viena, Austria},
  organization ={IAPR},
  annote = {An improper design of feature selection methods can often
    lead to incorrect conclusions. Moreover, it is not generally
    realised that functional values of the criterion guiding the
    search for the best feature set are random variables with some
    probability distribution. This contribution examines the influence
    of several estimation techniques on the consistency of the final
    result. We propose an entropy based measure which can assess the
    stability of feature selection methods with respect to
    perturbations in the data. Results show that filters achieve a
    better stability and performance if more samples are employed for
    the estimation, i.e., using leave-one-out cross-validation, for
    instance. However, the best results for wrappers are acquired with
    the 50/50 holdout validation.},
  keywords =    {Feature selection, stability, entropy},
  prestige =    {international},
  authorship =  {70-20-10 },
  project =     {INTAS 04-77-7347, 1M0567},
  psurl       = { fulltext (PDF),
                  poster (PDF) },
}