Measuring relevance between discrete and continuous features based on neighborhood mutual information

Volume: 38, Issue: 9, Pages: 10737 - 10750
Published: Sep 1, 2011
Abstract
Measures of relevance between features play an important role in classification and regression analysis. Mutual information has been proved an effective measure for decision tree construction and feature selection. However, there is a limitation in computing relevance between numerical features with mutual information due to problems of estimating probability density functions in high-dimensional spaces. In this work, we generalize Shannon's...
Paper Details
Title
Measuring relevance between discrete and continuous features based on neighborhood mutual information
Published Date
Sep 1, 2011
Volume
38
Issue
9
Pages
10737 - 10750
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