Automatically building a scikit learn estimator might include many conditional hyperparameters and also a very large amount of them (<100) [1]. However, perform

Automatically building a scikit learn estimator might include many conditional hyperparameters and also a very large amount of them (<100) [1]. However, performing joint architecture and hyperparameter search can be framed to be on a much simpler search space, e.g., for a recent paper that aims to automate the design of RNA molecules, we formulated a 14 dimensional search space which includes very little conditional hyperparameters [2]. The tools included in the repository are very broadly applicable and only a few of them are specifically targeted at neural architecture search. [1] https://www.kdnuggets.com/2016/08/winning-automl-challenge-auto-sklearn.html https://www.kdnuggets.com/2016/08/winning-automl-challenge-a... [2] https://openreview.net/forum?id=ByfyHh05tQ https://openreview.net/forum?id=ByfyHh05tQ