[MRG] Add fitted check for kde#16762
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rth merged 5 commits intoscikit-learn:masterfrom Apr 5, 2020
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albertcthomas
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Mar 29, 2020
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albertcthomas
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One small nitpick. Otherwise LGTM. Thanks @quangngd!
thomasjpfan
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Apr 2, 2020
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@quangngd I see this is your first time contributing, welcome!
sklearn/neighbors/tests/test_kde.py
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| def check_estimators_unfitted(name): |
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This test is not being run currently because it does not have a test_ prefix. We can try this:
@pytest.mark.parametrize('method', ['score_samples', 'sample'])
def test_check_is_fitted(method):
# Check that predict raises an exception in an unfitted estimator.
# Unfitted estimators should raise a NotFittedError.
rng = np.random.RandomState(0)
X = rng.randn(10, 2)
kde = KernelDensity()
with pytest.raises(NotFittedError):
getattr(kde, method)(X)
thomasjpfan
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Thank you for working on this, @quangngd
LGTM
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Reference Issues/PRs
Fixes #16613
What does this implement/fix? Explain your changes.
Add fitted check to
score_samplesandsamplefor kdeAny other comments?