The Bayesian Optimization Toolbox
Project description
GPyOpt
Gaussian process optimization using [GPy](http://sheffieldml.github.io/GPy/). Performs global optimization with different acquisition functions. Among other functionalities, it is possible to use GPyOpt to optimize physical experiments (sequentially or in batches) and to handle large data sets via sparse Gaussian process models.
[GPyOpt homepage](http://sheffieldml.github.io/GPyOpt/)
[Online documentation](http://gpyopt.readthedocs.org/en/latest/GPyOpt.html)
Getting started
Clone the repository in GitHub and add it to your PYTHONPATH.
Dependencies:
GPy
numpy
scipy
DIRECT (optional)
cma (optional)
pyDOE (optional)
Funding Acknowledgements
See GPy funding Acknowledgements
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