SafeOpt - Safe Bayesian Optimization
This code implements an adapted version of the safe, Bayesian optimization algorithm, SafeOpt [1], [2]. It also provides a more scalable implementation based on [3] as well as an implementation for the original algorithm in [4]. The code can be used to automatically optimize a performance measures subject to a safety constraint by adapting parameters. The prefered way of citing this code is by referring to [1] or [2].
Installation
The easiest way to install the necessary python libraries is by installing pip (e.g. apt-get install python-pip on Ubuntu) and running
pip install safeopt
Alternatively you can clone the repository and install it using
python setup.py install
Usage
The easiest way to get familiar with the library is to run the interactive example ipython notebooks!
Make sure that the ipywidgets module is installed. All functions and classes are documented on Read The Docs.
License
The code is licenced under the MIT license and free to use by anyone without any restrictions.
1 maintainer
Metadata
1 maintainer
Release files for safeopt 0.16
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
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| safeopt-0.16.tar.gz | 18.1 kB | Without provenance | Details for safeopt-0.16.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| safeopt-0.16-py2.py3-none-any.whl | Python 2, Python 3 | none | any | Details for safeopt-0.16-py2.py3-none-any.whl |
Total release size: 37.4 kB
Release files / safeopt-0.16.tar.gz
| Download URL | safeopt-0.16.tar.gz |
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| Size | 18.1 kB |
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Release files / safeopt-0.16-py2.py3-none-any.whl
| Download URL | safeopt-0.16-py2.py3-none-any.whl |
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| Tags | Python 2 Python 3 |
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