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On the Feature Selection Criterion Based on an Approximation of Multidimensional Mutual Information

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2 Author(s)
Balagani, K.S. ; Center for Secure Cyberspace, Comput. Sci., Louisiana Tech Univ., Ruston, LA, USA ; Phoha, V.V.

We derive the feature selection criterion presented in [1] and [2] from the multidimensional mutual information between features and the class. Our derivation: 1) specifies and validates the lower-order dependency assumptions of the criterion and 2) mathematically justifies the utility of the criterion by relating it to Bayes classification error.

Published in:

Pattern Analysis and Machine Intelligence, IEEE Transactions on  (Volume:32 ,  Issue: 7 )

Date of Publication:

July 2010

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