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Summary

This repository contains some basic code for Bayesian optimization

Installation

Install the current development version of scikit-learn (or sklearn version 0.18 once this is available)

git clone [email protected]:scikit-learn/scikit-learn.git
cd sklearn
sudo python setup.py install

Install bayesian_optimization

git clone [email protected]:jmetzen/bayesian_optimization.git
cd bayesian_optimization
sudo python setup.py install

Usage

Some usage examples are contained in the folder "examples". To reproduce the results from the ICML 2016 paper "Minimum Regret Search for Single- and Multi-Task Optimization", please execute the jupyter notebook "examples/mrs_evaluation.ipynb."

The directory bolero_bayes_opt contains modules which can be used with the external package BOLeRO, which is not yet open source and can thus be ignored for the moment.

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Bayesian optimization

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