FIX check that parameters validation happen in fit for KernelPCA #21567
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adrinjalali
reviewed
Nov 6, 2021
sklearn/decomposition/_kernel_pca.py
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| if self.fit_inverse_transform and self.kernel == "precomputed": | ||
| raise ValueError("Cannot fit_inverse_transform with a precomputed kernel.") |
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Please move this validation to the beginning of the fit method, so that it's done before _validate_data.
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Please also make sure this is tested in the test file.
|
Specifically, you need to change the test def test_kernel_pca_invalid_parameters():
"""Check that kPCA raises an error if the parameters are invalid
Tests fitting inverse transform with a precomputed kernel raises a
ValueError.
"""
with pytest.raises(ValueError):
estimator = KernelPCA(n_components=10, fit_inverse_transform=True, kernel="precomputed")
estimator.fit(np.random.randn(10, 10)) |
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jjerphan
requested changes
Nov 13, 2021
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Thank you for this contribution, @MaggieChege.
Some tiny changes can be introduced and this LGTM.
jjerphan
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Nov 15, 2021
glemaitre
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Nov 22, 2021
…kit-learn#21567) Co-authored-by: ciku <maggie@hellotractor.com>
glemaitre
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Nov 29, 2021
…kit-learn#21567) Co-authored-by: ciku <maggie@hellotractor.com>
samronsin
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Nov 30, 2021
…kit-learn#21567) Co-authored-by: ciku <maggie@hellotractor.com>
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Reference Issues/PRs
Addresses #21406
What does this implement/fix? Explain your changes.
Fix validate parameters in fit for KernelPCA
Any other comments?
#DataUmbrella