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[MRG+1] Fix description of l1_ratio for MultiTaskElasticNet #8343

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Merged
merged 2 commits into from
Feb 13, 2017
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[MRG+1] Fix description of l1_ratio for MultiTaskElasticNet #8343

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1736951
Fix l1_ratio documentation of MultiTaskElasticNet.
tguillemot Feb 12, 2017
39a9599
Update l1_ratio doc of MultiTaskElasticNetCV
tguillemot Feb 13, 2017
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8 changes: 4 additions & 4 deletions sklearn/linear_model/coordinate_descent.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1558,8 +1558,8 @@ class MultiTaskElasticNet(Lasso):

l1_ratio : float
The ElasticNet mixing parameter, with 0 < l1_ratio <= 1.
For l1_ratio = 0 the penalty is an L1/L2 penalty. For l1_ratio = 1 it
is an L1 penalty.
For l1_ratio = 1 the penalty is an L1/L2 penalty. For l1_ratio = 0 it
is an L2 penalty.
For ``0 < l1_ratio < 1``, the penalty is a combination of L1/L2 and L2.

fit_intercept : boolean
Expand Down Expand Up @@ -1873,8 +1873,8 @@ class MultiTaskElasticNetCV(LinearModelCV, RegressorMixin):

l1_ratio : float or array of floats
The ElasticNet mixing parameter, with 0 < l1_ratio <= 1.
For l1_ratio = 0 the penalty is an L1/L2 penalty. For l1_ratio = 1 it
is an L1 penalty.
For l1_ratio = 1 the penalty is an L1/L2 penalty. For l1_ratio = 0 it
is an L2 penalty.
For ``0 < l1_ratio < 1``, the penalty is a combination of L1/L2 and L2.
This parameter can be a list, in which case the different
values are tested by cross-validation and the one giving the best
Expand Down