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Hierarchical parameter definitions where sampling of a variable depends on the value of a parent parameter.
Distinct from Parameter Sampling: Distinct from general parameter sampling by introducing conditional dependencies and hierarchy logic.
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Hyperopt is a Python library for hyperparameter optimization designed to minimize scalar-valued objective functions. It operates as a stochastic search space engine that finds optimal input parameters by searching through real-valued, discrete, and conditional spaces. The framework distinguishes itself through its support for complex search space configurations, allowing for conditional parameter hierarchies where specific hyperparameters are sampled only if their parent parameters meet certain criteria. It is built as an asynchronous optimization framework, decoupling the generation of searc
Provides support for complex search spaces with conditional parameter hierarchies.