[MRG] Added documentation of intercept_ attribute of BayesianRidge #13429
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jnothman
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Mar 11, 2019
agramfort
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Mar 11, 2019
sklearn/linear_model/bayes.py
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| intercept_ : float | ||
| Independent term in decision function. Set to 0.0 if | ||
| ``fit_intercept = False``. This is not treated as a probabilistic | ||
| parameter and thus has no associated variance. |
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+1 to add this last sentence rather in description of fit_intercept parameter
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@agramfort & @jnothman, I have moved the line to |
jnothman
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…nRidge (scikit-learn#13429)" This reverts commit 1fa364d.
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…nRidge (scikit-learn#13429)" This reverts commit 1fa364d.
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Reference Issues/PRs
Fixes #13409
What does this implement/fix? Explain your changes.
Adds note that the intercept_ parameter does not have a probabilistic posterior associated, is only a point estimate. Ideally, it would optionally be treated as a probabilistic parameter, but this is non-trivial, as the prior should be uniform, which differs from the dependent parameters.