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Distance measures, especially between probability density functions, are essential in solving machine learning problems. Among classification and clustering, data reduction and selection are some of them. In the paper a new distance measure for comparing and selecting training datasets is described. The distance between two datasets is based on variance of entropy in groups obtained by clustering...
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