| bibtype |
C -
Conference Paper (international conference)
|
| ARLID |
0410760 |
| utime |
20240103182237.2 |
| mtime |
20060210235959.9 |
| ISBN |
3-540-41767-2 |
| title
(primary) (eng) |
Branch & Bound algorithm with partial prediction for use with recursive and non-recursive criterion forms |
| publisher |
| place |
Heidelberg |
| name |
Springer |
| pub_time |
2001 |
|
| specification |
|
| edition |
| name |
Lecture Notes in Computer Science. |
| volume_id |
2013 |
|
| serial |
| title
|
Advances in Pattern Recognition - ICAPR 2001. Proceedings |
| page_num |
425-434 |
| editor |
|
| editor |
|
| editor |
|
|
| keyword |
branch and bound |
| keyword |
search tree |
| keyword |
optimal subset selection |
| 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*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*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. |
|
| source |
|
| COSATI |
09K |
| COSATI |
09J |
| cas_special |
| project |
| project_id |
VS96063 |
| agency |
GA MŠk |
| ARLID |
cav_un_auth*0025066 |
|
| project |
| project_id |
ME 187 |
| agency |
GA MŠk |
| ARLID |
cav_un_auth*0028306 |
|
| project |
| project_id |
KSK1075601 |
| agency |
GA AV ČR |
| ARLID |
cav_un_auth*0027435 |
|
| research |
AV0Z1075907 |
| abstract
(eng) |
We introduce a novel algorithm for optimal feature selection. As opposed to our recent Fast Branch & Bound (FBB) algorithm the new algorithm is well suitable for use with recursive criterion forms. Even if the new algorithm does not operate as effectively as the FBB algorithm, it is able to find the optimum significantly faster than any other Branch & Bound. |
| action |
| ARLID |
cav_un_auth*0212824 |
| name |
ICAPR /2./ |
| place |
Rio de Janeiro |
| country |
BR |
| dates |
11.03.2001-14.03.2001 |
|
| RIV |
BD |
| department |
RO |
| permalink |
http://hdl.handle.net/11104/0130848 |
| ID_orig |
UTIA-B 20010229 |
| arlyear |
2001 |
| mrcbU10 |
2001 |
| mrcbU10 |
Heidelberg Springer |
| mrcbU12 |
3-540-41767-2 |
| mrcbU63 |
Advances in Pattern Recognition - ICAPR 2001. Proceedings 425 434 |
| mrcbU67 |
Singh S. 340 |
| mrcbU67 |
Murshed N. 340 |
| mrcbU67 |
Kropatsch W. 340 |
|