An Efficient, Parallelized Algorithm for Optimal Conditional Entropy-Based Feature Selection

In Machine Learning, feature selection is an important step in classifier design. It consists of finding a subset of features that is optimum for a given cost function. One possibility to solve feature selection is to organize all possible feature subsets into a Boolean lattice and to exploit the fa...

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