Confusion Matrix-Based Feature Selection
作者： A. Ralescu , Sofia Visa , B. Ramsay , E. VanDerKnaap
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摘要: This paper introduces a new technique for feature selection and illustrates it on real data set. Namely, the proposed approach creates subsets of attributes based two criteria: (1) individual have high discrimination (classification) power; (2) in subset are complementary that is, they misclassify different classes. The method uses information from confusion matrix evaluates one attribute at time.
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