bibtype |
C -
Conference Paper (international conference)
|
ARLID |
0348710 |
utime |
20240111140745.8 |
mtime |
20101101235959.9 |
title
(primary) (eng) |
The Problem of Fragile Feature Subset Preference in Feature Selection Methods and A Proposal of Algorithmic Workaround |
specification |
page_count |
4 s. |
media_type |
flash |
|
serial |
ARLID |
cav_un_epca*0348709 |
ISBN |
978-0-7695-4109-9 |
ISSN |
1051-4651 |
title
|
Proc. 2010 Int. Conf. on Pattern Recognition |
page_num |
4396-4399 |
publisher |
place |
Istanbul |
name |
IEEE Computer Society |
year |
2010 |
|
|
keyword |
feature selection |
keyword |
machine learning |
keyword |
over-fitting |
keyword |
classification |
keyword |
feature weights |
keyword |
weighted features |
keyword |
feature acquisition cost |
author
(primary) |
ARLID |
cav_un_auth*0101197 |
name1 |
Somol |
name2 |
Petr |
full_dept (cz) |
Rozpoznávání obrazu |
full_dept (eng) |
Department of Pattern Recognition |
department (cz) |
RO |
department (eng) |
RO |
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*0101091 |
name1 |
Grim |
name2 |
Jiří |
full_dept (cz) |
Rozpoznávání obrazu |
full_dept |
Department of Pattern Recognition |
department (cz) |
RO |
department |
RO |
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 |
full_dept (cz) |
Rozpoznávání obrazu |
full_dept |
Department of Pattern Recognition |
department (cz) |
RO |
department |
RO |
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 |
2C06019 |
agency |
GA MŠk |
country |
CZ |
ARLID |
cav_un_auth*0216518 |
|
project |
project_id |
GA102/07/1594 |
agency |
GA ČR |
ARLID |
cav_un_auth*0228611 |
|
project |
project_id |
GA102/08/0593 |
agency |
GA ČR |
ARLID |
cav_un_auth*0239567 |
|
project |
project_id |
1M0572 |
agency |
GA MŠk |
ARLID |
cav_un_auth*0001814 |
|
research |
CEZ:AV0Z10750506 |
abstract
(eng) |
We point out a problem inherent in the optimization scheme of many popular feature selection methods. It follows from the implicit assumption that higher feature selection criterion value always indicates more preferable subset even if the value difference is marginal. This assumption ignores the reliability issues of particular feature preferences, overfitting and feature acquisition cost. We propose an algorithmic extension applicable to many standard feature selection methods allowing better control over feature subset preference. We show experimentally that the proposed mechanism is capable of reducing the size of selected subsets as well as improving classifier generalization. |
action |
ARLID |
cav_un_auth*0265069 |
name |
20th International Conference on Pattern Recognition |
place |
Istanbul |
dates |
23.08.2010-26.08.2010 |
country |
TR |
|
reportyear |
2011 |
RIV |
BD |
permalink |
http://hdl.handle.net/11104/0189152 |
mrcbT16-q |
50 |
mrcbT16-s |
0.420 |
mrcbT16-y |
10.52 |
mrcbT16-x |
0.85 |
arlyear |
2010 |
mrcbU56 |
474kb |
mrcbU63 |
cav_un_epca*0348709 Proc. 2010 Int. Conf. on Pattern Recognition 978-0-7695-4109-9 1051-4651 4396 4399 Istanbul IEEE Computer Society 2010 |
|