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KMID : 0941520030030010112
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Korean Journal of Brain Science and Technology
2003 Volume.3 No. 1 p.112 ~ p.113
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Input Feature Selection by Mutual Information Based on Parzen Window
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Abstract
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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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