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[REF] Refactor Anomaly Detection Module into Submodules by Algorithm Family #2694
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In the follow-up commit, I make changes to the documentation and update all references where these algorithms are used. |
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Looks promising, but some minor remarks inline.
I guess, the deep_learning module will probably host most of the reconstruction and forecasting approaches later. We might decide to split it up. But this decision is for later.
aeon/anomaly_detection/sklearn_based/tests/test_one_class_svm.py
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Just the open comment from last time; otherwise, this looks good 👍🏼 |
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thanks for this, this module is still experimental so the refactor is fine.
Reference Issues/PRs
Fixes: #2663
What does this implement/fix? Explain your changes.
This PR addresses the issue of organizing the
anomaly_detection
module by refactoring the estimators into submodules based on their algorithm families.Does your contribution introduce a new dependency? If yes, which one?
Any other comments?
PR checklist
For all contributions
For new estimators and functions
__maintainer__
at the top of relevant files and want to be contacted regarding its maintenance. Unmaintained files may be removed. This is for the full file, and you should not add yourself if you are just making minor changes or do not want to help maintain its contents.For developers with write access