Scikit-Optimize: Bayesian Hyperparameter Optimization in Python

There are four optimization algorithms to try. You can run a simple random search over the parameters. Nothing fancy here but it is useful to have this option within the same API to compare if needed. Both of those methods as well as the one in the next section are examples of Bayesian Hyperparameter Optimization also known as Sequential Model-Based Optimization SMBO. The idea behind this approach is to estimate the user-defined objective function with the random forest, extra trees, or gradient boosted trees regressor.