Calculate Normalized Information Measures
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References
1. Hu, B.-G., He, R., and Yuan, X.-T., Information-Theoretic Measures for Objective Evaluation of Classifiers, submitted to a journal (2009); 2. B.-G. Hu, “Information Measure Toolbox for Classifier Evaluation on Open Source Software Scilab”, in: Proceedings of 2009 IEEE International Workshop on Open-source Software for Scientific Computation (OSSC-2009), pp. 179-184.
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The toolbox is to calculate normalized information measures from a given m by (m+1) confusion matrix for objective evaluations of an abstaining classifier. It includes total 24 normalized information measures based on three groups of definitions, that is, mutual information, information divergence, and cross entropy.
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