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


Autoria(s): Balagani, Kiran S; Phoha, Vir V; Iyengar, SS; Balakrishnan, N
Data(s)

01/05/2010

Resumo

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).

Formato

application/pdf

Identificador

http://eprints.iisc.ernet.in/27453/1/iee.pdf

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.

Publicador

IEEE

Relação

http://ieeexplore.ieee.org/search/srchabstract.jsp?tp=&arnumber=5395688&queryText%3DOn+Guo+and+Nixon%27s+Criterion+for+Feature+Subset+Selection%3A+Assumptions%2C+Implications%2C+and+Alternative+Options%26openedRefinements%3D*%26searchField%3DSearch+All

http://eprints.iisc.ernet.in/27453/

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Tipo

Journal Article

PeerReviewed