SMAC3 Bayesian Optimisation Integration [🆕 Search Method] 🥉 #212
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+ Custom config space is now utilising ConfigSpace + Classification.py is now divided in distinct Classifiers and Preprocesors for better understand and managmeent + Thorough documentation for users to add/modify anything
Get Search Space allows any search method to have access to the entire search space if needed.
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@PGijsbers A #Waiting tag would be greatly appreciated here. |
simonprovost
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PGijsbers
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Thank you! I will put this PR in the queue as you suggest :) |
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TODO:
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Update 15 jan. 2024 – NOT urgent at all. @PGijsbers – Given that the BO's implementation is utilising the asynchronous evaluator, I reckon we should call it async_BO instead of bayesian_optimisation, the same as async_ea. Your thoughts ? |
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BRIEF UDPATE: I intend to start working back on all this from the end of this month onwards. I have an important deadline for the 20th and had no time to look into those but will definitely afterward. Cheers for your patience! Simon |
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Hi @PGijsbers,
As proposed in #202, here is finally my final contribution probably for this year, the implementation of a brand-new Bayesian Optimisation search method based on SMAC3 compatible with GAMA under ConfigSpace search space setup as currently proposed in #210 🎉 🥇
While the PR follows the feature proposal in #202, it also includes an update to search algorithms to reduce pipeline duplication as per #211 🥈
Given that this PR is a suite from #210 and #211, here's a link that focuses exclusively on the most recent commits for this update: Link to PR updates 🥉
Thank you, and I look forward to hearing from you!
What contributions have been made
❌ DISCLAIMER ❌
Kindly refrain from merging this PR prior to ConfigSpace and Search Methods Improvements. I will need to perform a rebase from #211 before this PR can be merged!