A mutual information based feature selection algorithm

Cang, Shuang (2011) A mutual information based feature selection algorithm. In: 2011 4th International Conference on Biomedical Engineering and Informatics (BMEI). IEEE, pp. 2241-2245. ISBN 978-1-4244-9351-7

Full text not available from this repository.
Official URL: http://dx.doi.org/10.1109/BMEI.2011.6098784


The objective of the eliminating process is to reduce the size of the input feature set and at the same time to retain the class discriminatory information. This paper proposes and evaluates a new feature selection algorithm using information theory which is the mutual information (MI) between combinations of input features and the class instead of mutual information between a single input feature and the class for both continuous-valued and discrete-valued features. Comparison studies of new and previously published classification algorithms indicate that the proposed algorithm is robust, stable and efficient.

Item Type: Book Section
Uncontrolled Keywords: feature ranking, optimal feature set, mutual information and classification
Subjects: G900 Others in Mathematical and Computing Sciences
Department: Faculties > Business and Law > Newcastle Business School
Depositing User: Becky Skoyles
Date Deposited: 18 Dec 2018 10:20
Last Modified: 19 Nov 2019 09:52
URI: http://nrl.northumbria.ac.uk/id/eprint/37320

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