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A Heuristic Algorithm for Feature Selection Based on Optimization Techniques
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Author(s): A. M. Bagirov (University of Ballarat, Australia), A. M. Rubinov (University of Ballarat, Australia)and J. Yearwood (University of Ballarat, Australia)
Copyright: 2002
Pages: 14
Source title:
Heuristic and Optimization for Knowledge Discovery
Source Author(s)/Editor(s): Hussein A. Abbass (University of New South Wales, Australia), Charles S. Newton (University of New South Wales, Australia)and Ruhul Sarker (University of New South Wales, Australia)
DOI: 10.4018/978-1-930708-26-6.ch002
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Abstract
The feature selection problem involves the selection of a subset of features that will be sufficient for the determination of structures or clusters in a given dataset and in making predictions. This chapter presents an algorithm for feature selection, which is based on the methods of optimization. To verify the effectiveness of the proposed algorithm we applied it to a number of publicly available real-world databases. The results of numerical experiments are presented and discussed. These results demonstrate that the algorithm performs well on the datasets considered.
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