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On Guo and Nixon's Criterion for Feature Subset Selection: Assumptions, Implications,and Alternative Options

Balagani, Kiran S and Phoha, Vir V and Iyengar, SS and Balakrishnan, N (2010) On Guo and Nixon's Criterion for Feature Subset Selection: Assumptions, Implications,and Alternative Options. In: IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, 40 (3). pp. 651-655.

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Abstract

Guo and Nixon proposed a feature selection method based on maximizing I(x; Y),the multidimensional mutual information between feature vector x and class variable Y. Because computing I(x; Y) can be difficult in practice, Guo and Nixon proposed an approximation of I(x; Y) as the criterion for feature selection. We show that Guo and Nixon's criterion originates from approximating the joint probability distributions in I(x; Y) by second-order product distributions. We remark on the limitations of the approximation and discuss computationally attractive alternatives to compute I(x; Y).

Item Type: Journal Article
Additional Information: Copyright 2010 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Keywords: Entropic spanning graphs; feature selection; mutual information; Parzen window
Department/Centre: Others
Date Deposited: 07 Jun 2010 10:04
Last Modified: 19 Sep 2010 06:01
URI: http://eprints.iisc.ernet.in/id/eprint/27453

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