Introduction to the Tree-Structured Parzen Estimator Method

What is the Tree-Structured Parzen Estimator method?

The Tree-Structured Parzen Estimator (TPE) method is a powerful and intuitive approach for optimizing functions, often used in the process of hyperparameter tuning for ML algorithms to get the best performance. TPE combines the principles of Bayesian optimization and tree-based search, making it an efficient and effective method for finding the best set of hyperparameters for a given ML model.

At its core, TPE operates by modeling the relationship between hyperparameters and the performance of an ML model as a probabilistic distribution. It divides the search space into two parts: a good space and a bad space. The goal is to allocate more search effort to the good space, where better hyperparameter combinations are likely to be found.