Which useful python packages should be used to perform feature selection using Branch & Bound? The Branch & Bound algorithm has been proposed by Furnival and Wilson (1974) and does not look at all possible models, but rather list statistics for only the models with strongest fits for each number of predictors in the model. This is much less computationally intensive.

An alternative would be a package that does the same thing without computing thousands of models for all variable combinations.



closed as off-topic by whuber Dec 3 '18 at 23:08

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