bibtype |
C -
Conference Paper (international conference)
|
ARLID |
0317356 |
utime |
20240111140712.3 |
mtime |
20081216235959.9 |
title
(primary) (eng) |
Dynamic Oscillating Search Algorithm for Feature Selection |
specification |
page_count |
4 s. |
media_type |
www |
|
serial |
ARLID |
cav_un_epca*0317355 |
ISBN |
978-1-4244-2174-9 |
title
|
ICPR 2008 Proceedings (Int. Conf. on Pattern Recognition) |
page_num |
2308-2311 |
publisher |
place |
Tampa, Florida |
name |
IEEE Computer Society |
year |
2008 |
|
|
title
(cze) |
Dynamické oscilační vyhledávání pro výběr příznaků |
keyword |
feature selection |
keyword |
subset search |
keyword |
sequential search |
keyword |
oscillating search |
keyword |
subset size optimization |
author
(primary) |
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. |
|
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*0101091 |
name1 |
Grim |
name2 |
Jiří |
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*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. |
|
source |
|
cas_special |
project |
project_id |
1M0572 |
agency |
GA MŠk |
ARLID |
cav_un_auth*0001814 |
|
project |
project_id |
1ET400750407 |
agency |
GA AV ČR |
ARLID |
cav_un_auth*0001797 |
|
project |
project_id |
GA402/03/1310 |
agency |
GA ČR |
country |
CZ |
ARLID |
cav_un_auth*0009030 |
|
project |
project_id |
2C06019 |
agency |
GA MŠk |
country |
CZ |
ARLID |
cav_un_auth*0216518 |
|
research |
CEZ:AV0Z10750506 |
abstract
(eng) |
We introduce a new feature selection method suitable for non-monotonic criteria, i.e., for Wrapper-based feature selection. Inspired by Oscillating Search, the Dynamic Oscillating Search: (i) is deterministic, (ii) optimizes subset size, (iii) has built-in preference of smaller subsets, (iv) has higher optimization performance than other sequential methods. We show that the new algorithm is capable of over-performing older methods not only in criterion maximization ability but in some cases also in obtaining subsets that generalize better. |
abstract
(cze) |
Představujeme novou metodu výběru příznaků vhodnou pro nemonotonní kritéria, tedy pro výběr příznaků typu Wrapper. Inspirováno oscilačním vyhledáváním, nové dynamické oscilační vyhledávání: (i) je deterministické, (ii) optimalizuje velikost podmnožiny, (iii) má vestavěn mechanizmus upřednostnění menších podmnožin, (iv) má silnější optimalizační schopnost než ostatní sekvenční metody. Ukazujeme že nový algoritmus je schopen nejen nalézat řešení blíže optimu ve smyslu optimalizovaného kritéria, ale které také lépe zobecňuje. |
action |
ARLID |
cav_un_auth*0245342 |
name |
ICPR 2008 (Int. Conf. on Pattern Recognition) |
place |
Tampa, Florida |
dates |
07.12.2008-11.12.2008 |
country |
US |
|
reportyear |
2010 |
RIV |
BD |
permalink |
http://hdl.handle.net/11104/0167022 |
arlyear |
2008 |
mrcbU56 |
pdf 236kb |
mrcbU63 |
cav_un_epca*0317355 ICPR 2008 Proceedings (Int. Conf. on Pattern Recognition) 978-1-4244-2174-9 2308 2311 Tampa, Florida IEEE Computer Society 2008 |
|