Feature ranking and best feature subset using mutual information

This source preferred by Shuang Cang

Authors: Cang, S. and Partridge, D.

http://www.springerlink.com/content/b3gyjf726u6yet75/

Journal: Neural Computing and Applications

Volume: 13

Pages: 175-184

ISSN: 0941-0643

DOI: 10.1007/s00521-004-0400-9

A new algorithm for ranking the input features and obtaining the best feature subset is developed and illustrated in this paper. The asymptotic formula for mutual information and the expectation maximisation (EM) algorithm are used to developing the feature selection algorithm in this paper. We not only consider the dependence between the features and the class, but also measure the dependence among the features. Even for noisy data, this algorithm still works well. An empirical study is carried out in order to compare the proposed algorithm with the current existing algorithms. The proposed algorithm is illustrated by application to a variety of problems.

This data was imported from DBLP:

Authors: Cang, S. and Partridge, D.

Journal: Neural Computing and Applications

Volume: 13

Pages: 175-184

DOI: 10.1007/s00521-004-0400-9

This data was imported from Scopus:

Authors: Cang, S. and Partridge, D.

Journal: Neural Computing and Applications

Volume: 13

Issue: 3

Pages: 175-184

ISSN: 0941-0643

DOI: 10.1007/s00521-004-0400-9

A new algorithm for ranking the input features and obtaining the best feature subset is developed and illustrated in this paper. The asymptotic formula for mutual information and the expectation maximisation (EM) algorithm are used to developing the feature selection algorithm in this paper. We not only consider the dependence between the features and the class, but also measure the dependence among the features. Even for noisy data, this algorithm still works well. An empirical study is carried out in order to compare the proposed algorithm with the current existing algorithms. The proposed algorithm is illustrated by application to a variety of problems.

The data on this page was last updated at 04:42 on September 25, 2017.