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

0410760 - UTIA-B 20010229 RIV DE eng C - Conference Paper (international conference)
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]
R&D Projects: GA MŠMT VS96063; GA MŠMT ME 187; GA AV ČR KSK1075601
Institutional research plan: AV0Z1075907
Keywords : branch and bound * search tree * optimal subset selection
Subject RIV: BD - Theory of Information
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.
Permanent Link: http://hdl.handle.net/11104/0130848