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BayesianOptimization is a Python library that helps find the maximum (or minimum) of expensive or unknown objective functions using Bayesian optimization. This technique is especially useful for hyperparameter tuning in machine learning, where evaluating the objective function is costly. The library provides an easy-to-use API for defining bounds and optimizing over parameter spaces using probabilistic models like Gaussian Processes.
Features
- Black-box function optimization
- Easy API for defining parameter bounds
- Uses Gaussian Process regression
- Supports acquisition functions like UCB and EI
- Built-in logging and result tracking
- Ideal for hyperparameter tuning and experiments
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MIT LicenseFollow BayesianOptimization
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