Before revision: Bayesian Optimization (BO) is a successful methodology to tune the hyperparametersof machine learning algorithms. The user defines a metric of interest, such as the validation error, and BO finds the optimal hyperparametersthat minimize it.
After revision: Bayesian Optimization (BO) is a successful strategy to find good hyperparameters. BO defines an iterative procedure where a cross-validated metric is evaluated on promising hyperparameters. In practice, however, an improvement of the validation metric of interest, such as the validation error, and BO finds the optimal hyperparametersthat minimize it.