Feature selection in machine learning: Rényi min-entropy vs Shannon entropy

27 Jan 2020Catuscia PalamidessiMarco Romanelli

Feature selection, in the context of machine learning, is the process of separating the highly predictive feature from those that might be irrelevant or redundant. Information theory has been recognized as a useful concept for this task, as the prediction power stems from the correlation, i.e., the mutual information, between features and labels... (read more)

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