NDLI: On the suboptimal solutions using the adaptive branch and bound algorithm for feature selection

Content Provider	IEEE Xplore Digital Library
Author	Nakariyakul, S.
Copyright Year	2008
Description	Author affiliation: Dept. of Electr. & Comput. Eng., Thammasat Univ., Ampher Khlongluang (Nakariyakul, S.)
Abstract	The branch and bound algorithm is an optimal feature selection method that is well-known for its computational efficiency. The recently developed adaptive branch and bound algorithm has been shown to be several times faster than other versions of the branch and bound algorithm. If the optimality of the algorithm is allowed to be compromised, we can further improve the search speed by employing the look-ahead search strategy to eliminate many solutions deemed to be suboptimal early in the search. We investigate the effects of this scheme on the computational cost and suboptimal solutions obtained using the adaptive branch and bound algorithm and compare them with those using the basic branch and bound algorithm. Our experimental results for two different databases demonstrate that by setting the look-ahead parameter to an appropriate value, we can significantly reduce the search time of the adaptive branch and bound algorithm while retaining its optimal solutions.
Starting Page	384
Ending Page	389
File Size	265375
Page Count	6
File Format	PDF
ISBN	9781424422388
DOI	10.1109/ICWAPR.2008.4635809
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-08-30
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Dimensionality reduction Feature selection Databases Scattering Optimal subset search Suboptimal solutions Approximation algorithms Wavelet analysis Branch and bound algorithm Pattern recognition Ionosphere
Content Type	Text
Resource Type	Article

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