[scikit-learn] Using fit_intercept with sparse matrices

[Tom DLT]

note2:

The LogisticRegression and Ridge(solver='sag') code do fit the intercept
without breaking sparsity.

For other solvers in Ridge, in the case of a sparse X input, the solver
will automatically be changed to 'sag' and raise a warning.

Tom

2016-07-04 7:24 GMT+02:00 Tom Dupré la Tour <tom.duprelatour.10 at gmail.com>:

> note2:
>
> The LogisticRegression and Ridge(solver='sag') code do fit the intercept
> without breaking sparsity.
>
> For other solvers in Ridge, in the case of a sparse X input, the solver
> will automatically be changed to 'sag' and raise a warning.
> Le 2 juil. 2016 15:48, "Alexandre Gramfort" <
> alexandre.gramfort at telecom-paristech.fr> a écrit :
>
>> note:
>>
>> the Lasso and ElasticNet code do fit the intercept without breaking
>> sparsity.
>>
>> Alex
>> _______________________________________________
>> scikit-learn mailing list
>> scikit-learn at python.org
>> https://mail.python.org/mailman/listinfo/scikit-learn
>>
>
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mail.python.org/pipermail/scikit-learn/attachments/20160704/3193bb92/attachment.html>