Input feature selection by mutual information based on Parzen window
Pattern Analysis and Machine Intelligence, IEEE Transactions on, 24 (12):
1667--1671 (2002)Abstract
Mutual information is a good indicator of relevance between variables,
and have been used as a measure in several feature selection algorithms.
However, calculating the mutual information is difficult, and the
performance of a feature selection algorithm depends on the accuracy
of the mutual information. In this paper, we propose a new method
of calculating mutual information between input and class variables
based on the Parzen window, and we apply this to a feature selection
algorithm for classification problems.
