Bayesian Optimization for Anything: A high-level Bayesian optimization framework and model wrapping tool. It provides an easy-to-use interface between models and the python libraries Ax and BoTorch.
Project description
Bayesian Optimization for Anything
BOA is a high-level Bayesian optimization framework and model wrapping tool for providing an easy-to-use interface between models and the python libraries Ax and BoTorch
Key features
-
Model agnostic
- Can be used for models in any language (not just python)
- Can be used for Wrappers in any language (You don't even need to write any python!) See
Script Wrapper
for details on how to do that. - Simple to implement for new models, with minimal coding required
-
Scalable
- Can be used for simple models or complex models that require a lot of computational resources
- Scheduler to manage individual model runs
- Supports parallelization
-
Modular & customizable
- Can take advantages of the many features of Ax/BoTorch
- Customizable objective functions, multi-objective optimization, acquisition functions, etc
- Choice of built-in evaluation metrics, but it’s also easy to implement custom metrics
Install requirements
Docs | |
DOI | |
Conda Install | |
PyPI Install | |
Github Latest release | |
Github dev release | |
Build Status | |
Coverage |
Project details
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
boa-framework-0.10.2.tar.gz
(6.5 MB
view hashes)
Built Distribution
Close
Hashes for boa_framework-0.10.2-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 43dcf7491c140c9d180a1a2ed7ea27fdaf398635f34b7179dd1d2c952c428551 |
|
MD5 | e59db02493ea46645c50fd29379a8ee3 |
|
BLAKE2b-256 | 0d6da629ce5f107cc0dfd9e806916187c6ba7b7b482e663b2757460eb0f5f879 |