&hazrulakmal [MNT] fix remaining sklearn 1.3.0 compatibility issues
#4860
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fkiraly
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FYI @hazrulakmal, this is where I needed your PR #4832 Bit ironic given that a few days ago we were talking about how rare those aliases were... |
hazrulakmal
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…es with version speciefier and alias (#4867) In response to #4820 and maintainance in #4860, The current test_softdepds does not account for package versions and aliases. It only checks if dependencies can be imported using the package name via `import_modules` that only captures cases like "pmdarima" but not "pmdarmia<1.3". This resulted in failures if the **python_dependencies** tag had a package version bound or a different import name. This PR leverages `_check_soft_dependencies` to account for the drawbacks.
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sklearn 1.3.0 compatibility issuessklearn 1.3.0 compatibility issues
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There are some remaining compatibility issues from the
sklearn 1.3.0release which the pre-release testing did not catch. See #4778. This PR fixes those.ElasticEnsembleinstantiatedsklearnRandomizedSearchCVwithfloatn_iter, which sets off the parameter validation since 1.3.0. Fixed by coercing toint(rounding down)MatrixProfileClassifierfails due tosklearnbug AttributeError "Flags object has no attribute 'c_contiguous'" when using KNeighborsClassifier predict scikit-learn/scikit-learn#26768. This is 1.3.0 specific and appears fixed for (not yet released) 1.3.1, so added ansklearn!=1.3.0version requirement forMatrixProfileClassifierDepends on the bugfix #4867 to ensure the specifier
sklearn!=1.3.0is handled correctly.