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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.)

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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
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  • $\begingroup$ Do these implement the same Bayesian optimization or different BO methods? $\endgroup$ 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

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