domains / families / science / bayesian-optimizer

bayesian-optimizer

separate

Efficiently explores a parameter space to maximize a target metric using Gaussian Processes and the Upper Confidence Bound acquisition function.

When to use

• When experiments are expensive or time-consuming.
• To autonomously tune hyperparameters for a machine learning model.
• To optimize reaction conditions (temperature, pH, concentration).

Skill page

Source