I want to try and compare different optimization methods in some datasets. I know that in scikit-learn there are some corresponding functions for the grid and random search optimizations. However, I also need a package (or multiple ones) for different recent Bayesian optimization methods.

Are there any good and stable ones to use? Which packages do you recommend? (If any recent for grid/random search, it is also okay.)


Apart from the Scikit-Optimize package related to Scikit-Learn, following are some of the packages related to Bayesian optimization:

  1. GPyOpt
  2. pyGPGO
  3. Hyperopt
  4. bayesian-optimization
  5. safeopt
  6. RoBO
  • $\begingroup$ Do these implement the same Bayesian optimization or different BO methods? $\endgroup$ – Enes Altuncu Mar 3 '19 at 13:48
  • $\begingroup$ @EnesAltuncu each library implements a different set of algorithms. For better idea, maybe check the corresponding link above $\endgroup$ – programmer Mar 3 '19 at 14:12

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.