[MRG] Dynamically set n_quantiles to min(n_samples, n_quantiles) in QuantileTransformer #13333
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albertcthomas
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glemaitre
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Feb 28, 2019
| @@ -1260,6 +1260,12 @@ def test_quantile_transform_check_error(): | |||
| assert_raise_message(ValueError, | |||
| 'Expected 2D array, got scalar array instead', | |||
| transformer.transform, 10) | |||
| # check that a warning is raised is n_quantiles > n_samples | |||
| transformer = QuantileTransformer(n_quantiles=100) | |||
| assert_warns_message(UserWarning, | |||
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Could you use pytest to catch warning instead?
sklearn/preprocessing/data.py
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| n_samples = X.shape[0] | ||
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| if self.n_quantiles > n_samples: | ||
| self.n_quantiles = n_samples |
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It should be called n_quantiles_ isn't it?
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yes indeed I just fixed it
glemaitre
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Feb 28, 2019
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Thanks @glemaitre |
jnothman
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Feb 28, 2019
| n_samples = X.shape[0] | ||
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| if self.n_quantiles > n_samples: | ||
| warnings.warn("n_quantiles (%s) is greater than the total number " |
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I think this is more verbose than is helpful. "n_quantiles (%d) is being reduced to the number of samples (%d)" if you want to add another phrase explaining why, okay, but I think it's intuitively okay.
Co-Authored-By: albertcthomas <albertthomas88@gmail.com>
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Thanks @jnothman |
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…eTransformer (scikit-learn#13333)" This reverts commit 6dd1404.
xhluca
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…eTransformer (scikit-learn#13333)" This reverts commit 6dd1404.
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Fixes #13315
Values of
n_quantileslarger thann_sampleseither do not lead to a better approximation of the cdf estimator or to a wrong approximation. See #13315 for details.Don't know if this is considered as a bug or if this requires a deprecation cycle?