Tree-Structured Parzen Estimator

Tree-Structured Parzen Estimator is a sample-efficient method widely used in modern hyperparameter optimization. Unlike traditional surrogate-model approaches, it models good-performing and poor-performing regions with separate probability densities. This makes it especially effective in complex, conditional, and irregular hyperparameter spaces. Its flexibility is one reason it has become common in automated model selection and AutoML systems.