Literature DB >> 20489237

On the feature selection criterion based on an approximation of multidimensional mutual information.

Kiran S Balagani1, Vir V Phoha.   

Abstract

We derive the feature selection criterion presented in [CHECK END OF SENTENCE] and [CHECK END OF SENTENCE] 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.

Year:  2010        PMID: 20489237     DOI: 10.1109/TPAMI.2010.62

Source DB:  PubMed          Journal:  IEEE Trans Pattern Anal Mach Intell        ISSN: 0098-5589            Impact factor:   6.226


  5 in total

1.  Comparing the value of mammographic features and genetic variants in breast cancer risk prediction.

Authors:  Yirong Wu; Jie Liu; David Page; Peggy Peissig; Catherine McCarty; Adedayo A Onitilo; Elizabeth S Burnside
Journal:  AMIA Annu Symp Proc       Date:  2014-11-14

2.  A comprehensive methodology for determining the most informative mammographic features.

Authors:  Yirong Wu; Oguzhan Alagoz; Mehmet U S Ayvaci; Alejandro Munoz Del Rio; David J Vanness; Ryan Woods; Elizabeth S Burnside
Journal:  J Digit Imaging       Date:  2013-10       Impact factor: 4.056

3.  Using multidimensional mutual information to prioritize mammographic features for breast cancer diagnosis.

Authors:  Y Wu; D J Vanness; E S Burnside
Journal:  AMIA Annu Symp Proc       Date:  2013-11-16

4.  Feature selection by optimizing a lower bound of conditional mutual information.

Authors:  Hanyang Peng; Yong Fan
Journal:  Inf Sci (N Y)       Date:  2017-08-09       Impact factor: 6.795

5.  A kernel-based multivariate feature selection method for microarray data classification.

Authors:  Shiquan Sun; Qinke Peng; Adnan Shakoor
Journal:  PLoS One       Date:  2014-07-21       Impact factor: 3.240

  5 in total

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