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[MRG] Add support for Multimetric BayesSearchCV #1030
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Co-authored-by: Tim Head <[email protected]>
…alidation._fit_and_score * Update searchcv.py Further improvements for kernc previous commits. iid totally removed to prevent troubles with sklearn utils prettyprinting. prettyprinting looks for params when print to repl. Sklearn 0.24 has changed return value after cv, so i changed dict destructuring(a litttle bit dirty) * Update searchcv.py * Revert unrelated changes * PEP8 format; add comment * Revert reverting "unrelated changes" This is required to pass tests/test_searchcv.py with scikit-learn 0.24+. Co-authored-by: Kernc <[email protected]>
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Hello @QuentinSoubeyran! Thanks for updating this PR. We checked the lines you've touched for PEP 8 issues, and found: There are currently no PEP 8 issues detected in this Pull Request. Cheers! 🍻 Comment last updated at 2021-07-15 17:43:00 UTC |
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May 10, 2021
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Thanks and sorry for the wait. See a few notes below.
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Thank you for the review, no worries for the short wait. I integrated most of your suggestions. For the callable |
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Please merge this! |
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@Abdelgha-4 |
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Closed in favor of #1062 which should have a cleaner history |
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As discussed in PR #988 and issue #797, this PR implements support for multimetric scoring to
BayesSearchCV. Therefitparameter is used to drive the optimization process.Fixes:
Features:
scoringand callablescoringreturning a dict of scores toBayesSearchCVrefitto specify the score to use for optimisation. Callablerefit(accepted byGridSearchCV) are not supportedBayesSearchCV.multimetric_attributeI don't have much experience with the code style of scikit-learn/scikit-optimize, feel free to reformat the code as needed.