Comments (3)
From #393, framework is compatible without any issues.
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From #395, everything including all estimators is compatible without any issues. Minor restriction is that, in case of soft dependencies, we know this only for packages that already support numpy 2
, but I would not expect any major problems as interface code does not use numpy
typically, and if it does, only very superficially.
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Meaning, we can bump the numpy bound in 2.4.0.
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Related Issues (20)
- [ENH] general Johnson QPD regression wrapper to reduce proba to quantile predictions
- [ENH] proba regression: reduction to multiclass classification HOT 7
- [BUG] test_methods_p not handling getattr after shifting
- [ENH] Multiple link function support for GLMs HOT 3
- [BUG] `sklearn.utils._param_validation.InvalidParameterError` thrown when using max_iter parameter in various sklearn regressors HOT 1
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