1
$\begingroup$

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.

Thanks!

$\endgroup$

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

This question appears to be off-topic. The users who voted to close gave this specific reason:

  • "This question appears to be off-topic because EITHER it is not about statistics, machine learning, data analysis, data mining, or data visualization, OR it focuses on programming, debugging, or performing routine operations within a statistical computing platform. If the latter, you could try the support links we maintain." – whuber
If this question can be reworded to fit the rules in the help center, please edit the question.