[BUG] - bugfix, GridSearchCV scoring=None defaults to CRPS

[MaazAli8460]

If scoring= None, set it to CRPS().

Reference Issues/PRs

Fixes #1009.

What does this implement/fix? Explain your changes.

If scoring= None, set it to CRPS(). in _tuning.py

Does your contribution introduce a new dependency? If yes, which one?

No.

What should a reviewer concentrate their feedback on?

Did you add any tests for the change?

No. I don't think a separate test is necessary here.

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[Copilot]

Pull request overview

Fixes GridSearchCV crashing when scoring=None by applying the documented default metric (CRPS) during fitting.

Changes:

• Import CRPS into skpro.model_selection._tuning.
• In BaseGridSearch._fit, replace scoring=None with CRPS() before using scoring.name/scoring.get_tag.

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[Copilot]

Add a regression test to cover the scoring=None path (issue #1009). Without a test, this bug is likely to reappear since BaseGridSearch._fit relies on scoring.name/get_tag and will crash if scoring is ever left as None again. A minimal test can instantiate GridSearchCV with scoring=None, run fit, and assert that cv_results_ contains the expected CRPS-derived score column (e.g., mean_test_CRPS) and that no AttributeError is raised.

[fkiraly]

What exactly does this fix?

If it fixes a bug, please describe it - possibly in an issue, if it is longer - and also add a test for the bug being fixed.

[MaazAli8460]

@fkiraly Thanks for the review.
I have created an issue for this. Fixes #1009. It is also referenced here.
This PR fixes a bug that caused GridSearchCV to crash when scoring=None.
The change resolves scoring=None to CRPS() before scoring_name, matching the documented behavior.
Before the fix, BaseGridSearch._fit tried to read scoring.name while scoring was still None, causing: AttributeError: 'NoneType' object has no attribute 'name'.

Test Code:

import pandas as pd
from sklearn.model_selection import KFold

from skpro.model_selection import GridSearchCV
from skpro.regression.dummy import DummyProbaRegressor

X = pd.DataFrame({"x": [1, 2, 3, 4]})
y = pd.DataFrame({"y": [1.0, 2.0, 3.0, 4.0]})

gscv = GridSearchCV(
    estimator=DummyProbaRegressor(),
    cv=KFold(n_splits=2),
    param_grid={"strategy": ["empirical"]},
)

gscv.fit(X, y)
print(gscv.cv_results_)

In skpro\model_selection\ _tuning.py
BaseGridSearch._fit()
Before:

# scoring = check_scoring(self.scoring, obj=self)
        scoring = self.scoring
        scoring_name = f"test_{scoring.name}"

Raises error
AttributeError: 'NoneType' object has no attribute 'name'

After fix

# scoring = check_scoring(self.scoring, obj=self)
        scoring = self.scoring
        if scoring is None:
            scoring = CRPS()
        scoring_name = f"test_{scoring.name}"

On same test code

   mean_test_CRPS  mean_fit_time                     params  rank_test_CRPS
0            1.75       0.008404  {'strategy': 'empirical'}             1.0