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
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
File details
Details for the file GPyOpt-0.1.1.tar.gz.
File metadata
- Download URL: GPyOpt-0.1.1.tar.gz
- Upload date:
- Size: 23.8 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
13015702fcc2eb4db56b95ed486c561085212c637685aea4ae4c420295043549
|
|
| MD5 |
fd915d35daeff686b30123df9ac6fa77
|
|
| BLAKE2b-256 |
daa0e1ac6ec37e3d04538a4fb1bcf74b472a31ab7381904f5a3b50e2490ab442
|
