Upgrade scikit-learn #4248
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Upgrade scikit-learn #4248
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Codecov Report
@@ Coverage Diff @@
## main #4248 +/- ##
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+ Coverage 99.7% 99.7% +0.1%
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Files 349 349
Lines 38309 38320 +11
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+ Hits 38190 38201 +11
Misses 119 119
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eccabay
requested review from
jeremyliweishih,
fjlanasa,
MichaelFu512 and
remyogasawara
|
In further investigation of the imbalanced-learn error that caused its pinning, I found a workaround since the error is just in one of our tests. Pausing review on this PR until I can determine if this workaround allows me to unpin imbalanced-learn as well as upgrade scikit-learn instead of pinning it. |
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Looks like this is blocked until conda-forge/sktime-feedstock#94 is merged |
No longer blocked :-) |
chukarsten
approved these changes
Jul 24, 2023
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Closes #4247
** New and improved **
Upgrades to the most recent versions of scikit-learn and imbalanced-learn, plus updating sktime and vowpal-wabbit.
** Previous **
The newest version of scikit-learn is incompatible with the version of imbalanced-learn that we're pinned to. Unfortunately, imbalanced-learn must remain pinned due to lack of nullable type handling, so we can't upgrade scikit-learn. Once imbalanced-learn fixes their nullable type issues, we should be able to unpin both.
Nonetheless, this includes changes to Decision Tree and Extra Trees estimators to remove a deprecated "auto" argument that will be fully removed once we do upgrade to 1.3.0.