WilliamLwj/PyXAB
PyXAB - A Python Library for X-Armed Bandit and Online Blackbox Optimization Algorithms
This project helps data scientists and machine learning engineers efficiently find the best settings for their models or experiments, even when they don't know much about the underlying system. You provide a range of potential settings, and it iteratively suggests which ones to try next, learning from the results to quickly pinpoint the optimal configuration. This is ideal for anyone working with 'black-box' optimization problems.
127 stars. No commits in the last 6 months. Available on PyPI.
Use this if you need to optimize parameters for a complex system or machine learning model where direct mathematical analysis isn't possible, and you want to efficiently discover the best performing settings.
Not ideal if your optimization problem has a simple, well-understood mathematical structure that can be solved with traditional gradient-based methods.
Stars
127
Forks
30
Language
Python
License
MIT
Category
Last pushed
Oct 24, 2024
Commits (30d)
0
Dependencies
2
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