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A Branch and Bound Algorithm for Feature Subset Selection
Abstract
A feature subset selection algorithm based on branch and bound techniques is developed to select the best subset of m features from an n-feature set. Existing procedures for feature subset selection, such as sequential selection and dynamic programming, do not guarantee optimality of the selected feature subset. Exhaustive search, on the other hand, is generally computationally unfeasible. The present algorithm is very efficient and it selects the best subset without exhaustive search. Computational aspects of the algorithm are discussed. Results of several experiments demonstrate the very substantial computational savings realized. For example, the best 12-feature set from a 24-feature set was selected with the computational effort of evaluating only 6000 subsets. Exhaustive search would require the evaluation of 2 704 156 subsets.
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Cited by
A survey on feature selection methods
Chandrashekar, G., & Sahin, F. (2014) · Computers & Electrical Engineering · doi:10.1016/j.compeleceng.2013.11.024 · Cited by 5,189
(1998) · Cited by 3,476
An introduction to multisensor data fusion
Hall, D. L., & Llinas, J. (1997) · Proceedings of the IEEE · doi:10.1109/5.554205 · Cited by 2,629
Feature Selection: A Data Perspective
Li, J., Cheng, K., Wang, S., Morstatter, F., Trevino, R. P., Tang, J., & Liu, H. (2018) · ACM Computing Surveys · doi:10.1145/3136625 · Cited by 2,442
Chen, C. L. P., & Liu, Z. (2018) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2017.2716952 · Cited by 1,957
Metadata
- Authors
- Narendra, & Fukunaga
- Venue
- IEEE Transactions on Computers
- Published
- 1977-09
- Volume
- C-26
- Issue
- 9
- Pages
- 917-922
- ISSN
- 0018-9340 (ISSN-L)
- OpenAlex
- W1523989055
- Cited by
- 1,245
- References
- 0
- FWCI
- 3.32
- Type
- journal article
- Language
- en
- Open access
- closed
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- Narendra, & Fukunaga. (1977). A Branch and Bound Algorithm for Feature Subset Selection. IEEE Transactions on Computers. https://doi.org/10.1109/tc.1977.1674939
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