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[MRG] DOC update Ridge doc for sparse + fit_intercept #13530

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Mar 28, 2019
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[MRG] DOC update Ridge doc for sparse + fit_intercept #13530

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7 changes: 4 additions & 3 deletions sklearn/linear_model/ridge.py
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Expand Up @@ -290,7 +290,8 @@ def ridge_regression(X, y, alpha, sample_weight=None, solver='auto',


All last five solvers support both dense and sparse data. However, only
'sag' and 'saga' supports sparse input when`fit_intercept` is True.
'sag' and 'sparse_cg' supports sparse input when`fit_intercept` is
True.

.. versionadded:: 0.17
Stochastic Average Gradient descent solver.
Expand Down Expand Up @@ -651,8 +652,8 @@ class Ridge(_BaseRidge, RegressorMixin):
approximately the same scale. You can preprocess the data with a
scaler from sklearn.preprocessing.

All last five solvers support both dense and sparse data. However,
only 'sag' and 'saga' supports sparse input when `fit_intercept` is
All last five solvers support both dense and sparse data. However, only
'sag' and 'sparse_cg' supports sparse input when `fit_intercept` is
True.

.. versionadded:: 0.17
Expand Down