| bibtype |
J -
Journal Article
|
| ARLID |
0368741 |
| utime |
20240903170624.1 |
| mtime |
20111208235959.9 |
| WOS |
000293207900007 |
| SCOPUS |
83455221244 |
| title
(primary) (eng) |
Improving feature selection process resistance to failures caused by curse-of-dimensionality effects |
| specification |
|
| serial |
| ARLID |
cav_un_epca*0297163 |
| ISSN |
0023-5954 |
| title
|
Kybernetika |
| volume_id |
47 |
| volume |
3 (2011) |
| page_num |
401-425 |
| publisher |
| name |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
|
| keyword |
feature selection |
| keyword |
curse of dimensionality |
| keyword |
over-fitting |
| keyword |
stability |
| keyword |
machine learning |
| keyword |
dimensionality reduction |
| 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*0101171 |
| name1 |
Novovičová |
| name2 |
Jana |
| full_dept (cz) |
Rozpoznávání obrazu |
| full_dept |
Department of Pattern Recognition |
| department (cz) |
RO |
| department |
RO |
| institution |
UTIA-B |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0021092 |
| name1 |
Pudil |
| name2 |
P. |
| country |
CZ |
|
| source |
|
| cas_special |
| project |
| project_id |
1M0572 |
| agency |
GA MŠk |
| ARLID |
cav_un_auth*0001814 |
|
| project |
| project_id |
2C06019 |
| agency |
GA MŠk |
| country |
CZ |
| ARLID |
cav_un_auth*0216518 |
|
| project |
| project_id |
GA102/08/0593 |
| agency |
GA ČR |
| ARLID |
cav_un_auth*0239567 |
|
| research |
CEZ:AV0Z10750506 |
| abstract
(eng) |
The purpose of feature selection in machine learning is at least two-fold – saving measurement acquisition costs and reducing the negative effects of the curse of dimensionality with the aim to improve the accuracy of the models and the classification rate of classifiers with respect to previously unknown data. Yet it has been shown recently that the process of feature selection itself can be negatively affected by the very same curse of dimensionality – feature selection methods may easily over-fit or perform unstably. Such an outcome is unlikely to generalize well and the resulting recognition system may fail to deliver the expectable performance. In many tasks, it is therefore crucial to employ additional mechanisms of making the feature selection process more stable and resistant the curse of dimensionality effects. In this paper we discuss three different approaches to reducing this problem. |
| reportyear |
2012 |
| RIV |
IN |
| num_of_auth |
4 |
| mrcbC52 |
4 A O 4a 4o 20231122134815.9 |
| permalink |
http://hdl.handle.net/11104/0203004 |
| mrcbT16-e |
COMPUTERSCIENCECYBERNETICS |
| mrcbT16-f |
0.473 |
| mrcbT16-g |
0.033 |
| mrcbT16-h |
9.5 |
| mrcbT16-i |
0.0016 |
| mrcbT16-j |
0.277 |
| mrcbT16-k |
403 |
| mrcbT16-l |
61 |
| mrcbT16-q |
21 |
| mrcbT16-s |
0.307 |
| mrcbT16-y |
20.45 |
| mrcbT16-x |
0.61 |
| mrcbT16-4 |
Q2 |
| mrcbT16-B |
23.915 |
| mrcbT16-C |
17.500 |
| mrcbT16-D |
Q4 |
| mrcbT16-E |
Q3 |
| arlyear |
2011 |
| mrcbTft |
\nSoubory v repozitáři: somol-0368741.pdf, 0368741.pdf |
| mrcbU14 |
83455221244 SCOPUS |
| mrcbU34 |
000293207900007 WOS |
| mrcbU63 |
cav_un_epca*0297163 Kybernetika 0023-5954 Roč. 47 č. 3 2011 401 425 Ústav teorie informace a automatizace AV ČR, v. v. i. |
|