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[ENH] Update remaining registry
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#2198
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# Conflicts: # examples/classification/deep_learning.ipynb
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this all looks fine, but we could do with going over all base classes, make sure they have abstract constructors etc and resolve #2177
* registry refactor * all_estimators * comments and qc * fixes * fixes * exclude sklearn in docs * examples * examples
* Implemented COPOD for anomaly detection * fix: type annotations for python3.9 * fix: changed method decorator * test: soft dependencies check * [DOC] Add JMLR paper to readme (#2203) * add paper * add paper * [DOC, ENH] Add WEASEL v2 and Human Activity Challenge Papers (#2204) * add WEASEL v2 paper * add ECML challenge * [ENH] Update remaining `registry` files (#2198) * registry refactor * all_estimators * comments and qc * fixes * fixes * exclude sklearn in docs * examples * examples * [MNT] Changes in preparation for update to `numpy` 2 (#1813) * numpy 2 * Update pyproject.toml * bound * scipy bound * correct method * not 2.1.0 * comment deps * comment deps * comment deps * make numpy 2.0 compatible * restore current numpy bound * revert to main pyproject * Empty commit for CI --------- Co-authored-by: aadya940 <aadya@unify.ai> Co-authored-by: Tony Bagnall <a.j.bagnall@soton.ac.uk> Co-authored-by: Tony Bagnall <ajb@uea.ac.uk> Co-authored-by: TonyBagnall <TonyBagnall@users.noreply.github.com> * [ENH] Split up rocket estimators (#2207) * split up rocket * test params * test params * test params * more fixes for float_ (#2215) * Implemented COPOD for anomaly detection * update: added new test cases * changes: clean up --------- Co-authored-by: Tony Bagnall <a.j.bagnall@soton.ac.uk> Co-authored-by: Patrick Schäfer <patrick.schaefer@hu-berlin.de> Co-authored-by: Matthew Middlehurst <pfm15hbu@gmail.com> Co-authored-by: aadya940 <aadya@unify.ai> Co-authored-by: Tony Bagnall <ajb@uea.ac.uk> Co-authored-by: TonyBagnall <TonyBagnall@users.noreply.github.com>
registry
utils.base
and reworked into a dictionary.all_estimators
has been simplified a bit and moved toutils.discovery
(same import as sklearn)check_tag_value
to help validating the value of singular tags