[MRG+1] Fix precomputation of Gram matrix in Lars#5359
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agramfort merged 1 commit intoscikit-learn:masterfrom Jun 13, 2017
Merged
[MRG+1] Fix precomputation of Gram matrix in Lars#5359agramfort merged 1 commit intoscikit-learn:masterfrom
agramfort merged 1 commit intoscikit-learn:masterfrom
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I would say raise an error instead of a warning but it depends on how much we want to nurse the user.
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I was thinking about avoiding an error when a user changes Lars(precompute=G).fit(X, y) into LarsCV(precompute=G).fit(X, y). But it is kind of nursing.
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LGTM @TomDLT can you update what's new to document the bug fix? |
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done |
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+1 for MRG when CIs are happy thx @TomDLT |
arthurmensch
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To me it would make more sense to explicitely feed the gram matrix in the .fit but I reckon this has little usage anyway. LGTM
| return Gram | ||
| def _get_gram(self, precompute, X, y): | ||
| if (not hasattr(precompute, '__array__')) and ( | ||
| (precompute is True) or |
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CIs are happy here |
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@TomDLT you need to rebase |
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@TomDLT please fix conflicts here and then let's merge. |
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The AppVeyor failures are on master #9111 |
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thanks @TomDLT |
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This is a fix for the bug reported in #1856.
The parameter
precompute(in RandomizedLasso, Lars, LarsLasso, LarsCV and LarsLassoCV) were not consistent and some values proposed in the docstrings (False, array) could raise errors.This PR includes the following steps:
lars_path, to allowGram=TrueandGram=False._get_grammethod, to handleprecomputein the same way in every class.precompute, in LarsCV and LarsLassoCV.test_randomized_l1.pyis also updated to be shorter (from 1.582s to 0.817s).test_least_angle.pygoes from 1.305s to 1.465s.