PyImpetus - A Markov Blanket based new SOTA feature selection algorithm for python

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PyImpetus is a Markov Blanket based feature selection algorithm that selects a subset of features by considering their performance both individually as well as a group. This allows the algorithm to not only select the best set of features but also select the best set of features that play well with each other. For example, the best performing feature might not play well with others while the remaining features, when taken together could out-perform the best feature. PyImpetus takes this into account and produces the best possible combination. Thus, the algorithm provides a minimal feature subset. So, you do not have to decide on how many features to take. PyImpetus selects the optimal set for you.