Branch & Bound algorithm with partial prediction for use with recursive and non-recursive criterion forms

0410760 - UTIA-B 20010229 RIV DE eng C - Konferenční příspěvek (zahraniční konf.)
Somol, Petr - Pudil, Pavel - Grim, Jiří
Branch & Bound algorithm with partial prediction for use with recursive and non-recursive criterion forms.
Heidelberg: Springer, 2001. Lecture Notes in Computer Science., 2013. ISBN 3-540-41767-2. In: Advances in Pattern Recognition - ICAPR 2001. Proceedings. - (Singh, S.; Murshed, N.; Kropatsch, W.), s. 425-434
[ICAPR /2./. Rio de Janeiro (BR), 11.03.2001-14.03.2001]
Grant CEP: GA MŠMT VS96063; GA MŠMT ME 187; GA AV ČR KSK1075601
Výzkumný záměr: AV0Z1075907
Klíčová slova: branch and bound * search tree * optimal subset selection
Kód oboru RIV: BD - Teorie informace
http://library.utia.cas.cz/separaty/historie/somol-branch & bound algorithm with partial prediction for use with recursive and non-recursive criterion forms.pdf

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.
Trvalý link: http://hdl.handle.net/11104/0130848