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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 Documentation Status
DOI DOI
Conda Install Conda Version
PyPI Install PyPI version
Github Latest release Github release
Github dev release Github tag
Build Status ci
Coverage codecov

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