bibtype M - Monography Chapter
ARLID 0410987
utime 20240103182253.8
mtime 20060210235959.9
ISBN 1-4020-0953-4
title (primary) (eng) Recent feature selection methods in statistical pattern recognition
publisher
place Dordrecht
name Kluwer
pub_time 2003
specification
page_count 51 s.
serial
title Pattern Recognition and String Matching
page_num 1-51
editor
name1 Chen
name2 D.
editor
name1 Cheng
name2 X.
keyword pattern recognition
keyword feature selection
keyword search methods
author (primary)
ARLID cav_un_auth*0101182
name1 Pudil
name2 Pavel
institution UTIA-B
full_dept Department of Pattern Recognition
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0101171
name1 Novovičová
name2 Jana
institution UTIA-B
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0101197
name1 Somol
name2 Petr
institution UTIA-B
full_dept Department of Pattern Recognition
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
COSATI 09K
COSATI 12B
cas_special
project
project_id GA402/01/0981
agency GA ČR
ARLID cav_un_auth*0008962
project
project_id KSK1019101
agency GA AV ČR
ARLID cav_un_auth*0000219
research CEZ:AV0Z1075907
abstract (eng) The chapter is devoted to the problem of feature selection in statistical pattern recognition. A number of feature subset search strategies is reviewed, analyzed and compared. New algorithms are described (Fast Branch and Bound, Branch and Bound Algorithm with Partial Prediction, Floating Search, Adaptive Floating Search). Two feature selection methods based on approximating the unknown class conditional densities by finite mixtures of the factorized densities are presented.
RIV BC
department RO
permalink http://hdl.handle.net/11104/0131074
ID_orig UTIA-B 20020201
arlyear 2003
mrcbU10 2003
mrcbU10 Dordrecht Kluwer
mrcbU12 1-4020-0953-4
mrcbU63 Pattern Recognition and String Matching 1 51
mrcbU67 Chen D. 340
mrcbU67 Cheng X. 340