Choosing the right parameters for a machine learning model is almost more of an art than a science. Kaggle competitors spend considerable time on tuning their model in the hopes of winning competitions, and proper model selection plays a huge part in that. It is remarkable then, that the industry standard algorithm for selecting hyperparameters, is something as simple as random search. The strength of random search lies in its simplicity. Given a learner \(\mathcal{M}\), with parameters \(\ma...| Thomas Huijskens