Bayesian Optimization, Machine Learning, AI, Hyperparameter Tuning.
underfitting. The aim of hyperparameter optimization in machine learning is to find the hyperparameters of a given ML algorithm that return the best performance as measured on a validation set. Below you can see examples of hyperparameters for two algorithms, random forest and gradient boosting