期刊
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
卷 24, 期 12, 页码 1667-1671出版社
IEEE COMPUTER SOC
DOI: 10.1109/TPAMI.2002.1114861
关键词
feature selection; mutual information; Parzen window
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.
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