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[P] Command-line tool for Bayesian black-box optimization

Hi r/machinelearning,

I wrote a CLI tool that runs black-box Bayesian optimization on an arbitrary shell command.

https://gitlab.com/gwerbin/bayesopt-cli

Usage: 1. Define a “space” to optimize over, using the Scikit-optimize YAML specification format 2. Run the bayesopt tool 3. Save a summary of results from stdout, and/or load the full saved “optimization result” object from disk

There is an example in the repo to hopefully make this usage more clear.

Internally, it’s just a wrapper for Scikit-optimize, which has been giving me good results. This code could easily be extended to use Hyperopt’s TPE optimizer, but I wanted to start simple with one backend.

It also lets you emit output from your command as JSON, with an option to extract a number from it using JMESPath.

Unfortunately installation is annoying at the moment. The Scikit-optimize devs seem to have abandoned the project, so this relies on a patched fork of the latest version. Hopefully that will get straightened out (community fork, maybe?) and I can distribute this like a normal Python package.

Let me know what you think! Is this useful to anyone other than me?

submitted by /u/nerdponx
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.