This example assumes basic familiarity with scikit-learn. Search for parameters of machine learning models that result in best cross-validation performance is necessary in almost all practical cases to get a model with best generalization estimate. A standard approach in scikit-learn is using GridSearchCV class, which takes a set of values for every parameter to try, and simply enumerates all combinations of parameter values. The complexity of such search grows exponentially with addition of new parameters. A more scalable approach is using RandomizedSearchCV, which however does not take advantage of the structure of a search space.