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Results tagged with bayesian-optimization
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user 22784
For questions related to Bayesian optimization (BO), which is a technique used to model an unknown function (that is expensive to evaluate), based on concepts of a surrogate model (which is usually a Gaussian process, which models the unknown function), Bayesian inference (to update the Gaussian process) and an acquisition function (which guides the Bayesian inference). BO can be used for hyper-parameter optimization.
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Are there Python packages for recent Bayesian optimization methods? [closed]
I want to try and compare different optimization methods in some datasets. I know that in scikit-learn there are some corresponding functions for the grid and random search optimizations. However, I a …
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