Welcome to the tag category page for Random forest!
Optuna is an automatic hyperparameter optimization software framework that is designed for machine learning. It features an imperative, define-by-run style interface and supports various state-of-the-art optimization algorithms, including Bayesian optimization. Optuna enables automatic searches and finds optimal hyperparameters by trial and error, which leads to excellent performance. Moreover, it supports imperative parameter definition, which provides more flexibility, and features a pruning mechanism that monitors each trial's learning curves and determines the sets of hyperparameters that will not lead to good results. Currently, the software can be used in Python and is available on GitHub. Overall, Optuna is a powerful tool that is widely used and highly recommended for hyperparameter optimization in the field of machine learning.
