Welcome to boa’s documentation!#
BOA’s is 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.
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
Important
This site is still under construction. More content will be added soon!
Contents#
- User guide
- Examples
- Running an Experiment from Command Line (Python Wrapper)
- Running an R Script with BOA
- BOA Provided Visualizations
- Running BOA Optimization Directly in Python
- Loading BOA from JSON and Plotting Results
- Running a Multi Objective Optimization Directly in Python
- Multi Objective Loading BOA from JSON and Plotting Results
- Example FETCH3 optimization results
- Troubleshooting
- Changelog
- Code reference
- Gallery
- Contributing to boa