Feature Selection Based on Information Theory, Consistency and Separability Indices
نویسندگان
چکیده
Two new feature selection methods are introduced, the first based on separability criterion, the second on consistency index that includes interactions between the selected subsets of features. Comparison of accuracy was made against information-theory based selection methods on several datasets training neurofuzzy and nearest neighbor methods on various subsets of selected features. Methods based on separability seem to be most promising.
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