0410787 20240103182239.220060210235959.9 6 s. cav_un_epca*02573890167-8655234 (2002)487-492Elsevier pattern recognition feature selection loating search algorithms cav_un_auth*0101182 Pudil Pavel UTIA-B Department of Pattern Recognition Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0101171 Novovičová Jana UTIA-B Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0101197 Somol Petr UTIA-B Department of Pattern Recognition Ústav teorie informace a automatizace AV ČR, v. v. i. 09K 12B GA402/01/0981 GA ČR cav_un_auth*0008962 CEZ:AV0Z1075907 Recent advances in the statistical methodology for selecting optimal subsets of features for data representation and classification are presented. The paper attempts to provide a guideline which approach to choose with respect to the extent of a priori knowledge of the problem. Two basic approaches are reviewed and the conditions under which they should be used are specified. A consulting system aimed to guide a user to choose a proper method for the problem at hand is being prepared. BB RO http://hdl.handle.net/11104/0130874 UTIA-B 20020001 2002 cav_un_epca*0257389 Pattern Recognition Letters 0167-8655 1872-7344 Roč. 23 č. 4 2002 487 492 Elsevier