@InProceedings{Krizek-PPGT2005,
  IS = { zkontrolovano 06 Jan 2006 },
  UPDATE  = { 2005-06-21 },
  author =      {K{\v r}{\'\i }{\v z}ek, Pavel and
                 Hlav{\' a}{\v c}, V{\' a}clav and
                 Josef Kittler},
  title =       {Feature selection for genetic microarray data},
  year =        {2005},
  pages =       {77--80},
  booktitle =   {PPGT 2005: Proceedings of the Prague Post Genome
                 Technology Workshop 2005},
  editor =      {Hlav{\' a}{\v c}, V{\' a}clav and Hiedeki Kambara},
  publisher =   {Czech Pattern Recognition Society},
  address =     {Prague, Czech Republic},
  isbn =        {80-01-03239-6},
  book_pages =  {84},
  month =       {June},
  day =         {6--7},
  venue =       {Prague, Czech Republic},
  organization ={Hitachi, Ltd.},
  prestige =    {international},
  authorship =  {80-10-10},
  project =     {CTU 0505613, GACR 102/03/0440, INTAS 04-77-7347},
  psurl       = {[PDF, 250
kB]},
  keywords =    {Feature selection, wrapper, microarray, gene expression},
  annote =      {This paper reports on applying state-of-the-art feature
  selection techniques to genetic microarray data. The wrapper based
  feature selection approach is studied. Frequently utilized learning
  algorithms are employed as an objective function. Selected subsets of
  genes are examined not only for training sets but also for independent
  test sets. Generally, the evaluation of selected subsets of genes is
  worse on test data than the training data leave-one-out cross-validation.},
}