8000 DOC replace e.g. by i.e. in fit_intercept docstring by amueller · Pull Request #14594 · scikit-learn/scikit-learn · GitHub
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DOC replace e.g. by i.e. in fit_intercept docstring #14594

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Merged
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Aug 7, 2019
Merged

DOC replace e.g. by i.e. in fit_intercept docstring #14594

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2 changes: 1 addition & 1 deletion sklearn/linear_model/base.py
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Expand Up @@ -371,7 +371,7 @@ class LinearRegression(LinearModel, RegressorMixin, MultiOutputMixin):
fit_intercept : boolean, optional, default True
whether to calculate the intercept for this model. If set
to False, no intercept will be used in calculations
(e.g. data is expected to be already centered).
(i.e. data is expected to be centered).

normalize : boolean, optional, default False
This parameter is ignored when ``fit_intercept`` is set to False.
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4 changes: 2 additions & 2 deletions sklearn/linear_model/bayes.py
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Expand Up @@ -76,7 +76,7 @@ class BayesianRidge(LinearModel, RegressorMixin):
The intercept is not treated as a probabilistic parameter
and thus has no associated variance. If set
to False, no intercept will be used in calculations
(e.g. data is expected to be already centered).
(i.e. data is expected to be centered).


normalize : boolean, optional, default False
Expand Down Expand Up @@ -425,7 +425,7 @@ class ARDRegression(LinearModel, RegressorMixin):
fit_intercept : boolean, optional
whether to calculate the intercept for this model. If set
to false, no intercept will be used in calculations
(e.g. data is expected to be already centered).
(i.e. data is expected to be centered).
Default is True.

normalize : boolean, optional, default False
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14 changes: 7 additions & 7 deletions sklearn/linear_model/coordinate_descent.py
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Expand Up @@ -820,7 +820,7 @@ class Lasso(ElasticNet):
fit_intercept : boolean, optional, default True
Whether to calculate the intercept for this model. If set
to False, no intercept will be used in calculations
(e.g. data is expected to be already centered).
(i.e. data is expected to be centered).

normalize : boolean, optional, default False
This parameter is ignored when ``fit_intercept`` is set to False.
Expand Down Expand Up @@ -1258,7 +1258,7 @@ class LassoCV(LinearModelCV, RegressorMixin):
fit_intercept : boolean, default True
whether to calculate the intercept for this model. If set
to false, no intercept will be used in calculations
(e.g. data is expected to be already centered).
(i.e. data is expected to be centered).

normalize : boolean, optional, default False
This parameter is ignored when ``fit_intercept`` is set to False.
Expand Down Expand Up @@ -1430,7 +1430,7 @@ class ElasticNetCV(LinearModelCV, RegressorMixin):
fit_intercept : boolean
whether to calculate the intercept for this model. If set
to false, no intercept will be used in calculations
(e.g. data is expected to be already centered).
(i.e. data is expected to be centered).

normalize : boolean, optional, default False
This parameter is ignored when ``fit_intercept`` is set to False.
Expand Down Expand Up @@ -1635,7 +1635,7 @@ class MultiTaskElasticNet(Lasso):
fit_intercept : boolean
whether to calculate the intercept for this model. If set
to false, no intercept will be used in calculations
(e.g. data is expected to be already centered).
(i.e. data is expected to be centered).

normalize : boolean, optional, default False
This parameter is ignored when ``fit_intercept`` is set to False.
Expand Down Expand Up @@ -1821,7 +1821,7 @@ class MultiTaskLasso(MultiTaskElasticNet):
fit_intercept : boolean
whether to calculate the intercept for this model. If set
to false, no intercept will be used in calculations
(e.g. data is expected to be already centered).
(i.e. data is expected to be centered).

normalize : boolean, optional, default False
This parameter is ignored when ``fit_intercept`` is set to False.
Expand Down Expand Up @@ -1962,7 +1962,7 @@ class MultiTaskElasticNetCV(LinearModelCV, RegressorMixin):
fit_intercept : boolean
whether to calculate the intercept for this model. If set
to false, no intercept will be used in calculations
(e.g. data is expected to be already centered).
(i.e. data is expected to be centered).

normalize : boolean, optional, default False
This parameter is ignored when ``fit_intercept`` is set to False.
Expand Down Expand Up @@ -2136,7 +2136,7 @@ class MultiTaskLassoCV(LinearModelCV, RegressorMixin):
fit_intercept : boolean
whether to calculate the intercept for this model. If set
to false, no intercept will be used in calculations
(e.g. data is expected to be already centered).
(i.e. data is expected to be centered).

normalize : boolean, optional, default False
This parameter is ignored when ``fit_intercept`` is set to False.
Expand Down
12 changes: 6 additions & 6 deletions sklearn/linear_model/least_angle.py
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Expand Up @@ -768,7 +768,7 @@ class Lars(LinearModel, RegressorMixin, MultiOutputMixin):
fit_intercept : boolean
Whether to calculate the intercept for this model. If set
to false, no intercept will be used in calculations
(e.g. data is expected to be already centered).
(i.e. data is expected to be centered).

verbose : boolean or integer, optional
Sets the verbosity amount
Expand Down Expand Up @@ -987,7 +987,7 @@ class LassoLars(Lars):
fit_intercept : boolean
whether to calculate the intercept for this model. If set
to false, no intercept will be used in calculations
(e.g. data is expected to be already centered).
(i.e. data is expected to be centered).

verbose : boolean or integer, optional
Sets the verbosity amount
Expand Down Expand Up @@ -1146,7 +1146,7 @@ def _lars_path_residues(X_train, y_train, X_test, y_test, Gram=None,
fit_intercept : boolean
whether to calculate the intercept for this model. If set
to false, no intercept will be used in calculations
(e.g. data is expected to be already centered).
(i.e. data is expected to be centered).

positive : boolean (default=False)
Restrict coefficients to be >= 0. Be aware that you might want to
Expand Down Expand Up @@ -1232,7 +1232,7 @@ class LarsCV(Lars):
fit_intercept : boolean
whether to calculate the intercept for this model. If set
to false, no intercept will be used in calculations
(e.g. data is expected to be already centered).
(i.e. data is expected to be centered).

verbose : boolean or integer, optional
Sets the verbosity amount
Expand Down Expand Up @@ -1446,7 +1446,7 @@ class LassoLarsCV(LarsCV):
fit_intercept : boolean
whether to calculate the intercept for this model. If set
to false, no intercept will be used in calculations
(e.g. data is expected to be already centered).
(i.e. data is expected to be centered).

verbose : boolean or integer, optional
Sets the verbosity amount
Expand Down Expand Up @@ -1615,7 +1615,7 @@ class LassoLarsIC(LassoLars):
fit_intercept : boolean
whether to calculate the intercept for this model. If set
to false, no intercept will be used in calculations
(e.g. data is expected to be already centered).
(i.e. data is expected to be centered).

verbose : boolean or integer, optional
Sets the verbosity amount
Expand Down
6 changes: 3 additions & 3 deletions sklearn/linear_model/omp.py
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Expand Up @@ -556,7 +556,7 @@ class OrthogonalMatchingPursuit(LinearModel, RegressorMixin, MultiOutputMixin):
fit_intercept : boolean, optional
whether to calculate the intercept for this model. If set
to false, no intercept will be used in calculations
(e.g. data is expected to be already centered).
(i.e. data is expected to be centered).

normalize : boolean, optional, default True
This parameter is ignored when ``fit_intercept`` is set to False.
Expand Down Expand Up @@ -701,7 +701,7 @@ def _omp_path_residues(X_train, y_train, X_test, y_test, copy=True,
fit_intercept : boolean
whether to calculate the intercept for this model. If set
to false, no intercept will be used in calculations
(e.g. data is expected to be already centered).
(i.e. data is expected to be centered).

normalize : boolean, optional, default True
This parameter is ignored when ``fit_intercept`` is set to False.
Expand Down Expand Up @@ -770,7 +770,7 @@ class OrthogonalMatchingPursuitCV(LinearModel, RegressorMixin):
fit_intercept : boolean, optional
whether to calculate the intercept for this model. If set
to false, no intercept will be used in calculations
(e.g. data is expected to be already centered).
(i.e. data is expected to be centered).

normalize : boolean, optional, default True
This parameter is ignored when ``fit_intercept`` is set to False.
Expand Down
6 changes: 3 additions & 3 deletions sklearn/linear_model/ridge.py
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9B24
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Expand Up @@ -631,7 +631,7 @@ class Ridge(_BaseRidge, RegressorMixin):
fit_intercept : bool, default True
Whether to calculate the intercept for this model. If set
to false, no intercept will be used in calculations
(e.g. data is expected to be already centered).
(i.e. data is expected to be centered).

normalize : boolean, optional, default False
This parameter is ignored when ``fit_intercept`` is set to False.
Expand Down Expand Up @@ -1601,7 +1601,7 @@ class RidgeCV(_BaseRidgeCV, RegressorMixin):
fit_intercept : bool, default True
Whether to calculate the intercept for this model. If set
to false, no intercept will be used in calculations
(e.g. data is expected to be already centered).
(i.e. data is expected to be centered).

normalize : boolean, optional, default False
This parameter is ignored when ``fit_intercept`` is set to False.
Expand Down Expand Up @@ -1714,7 +1714,7 @@ class RidgeClassifierCV(LinearClassifierMixin, _BaseRidgeCV):
fit_intercept : boolean
Whether to calculate the intercept for this model. If set
to false, no intercept will be used in calculations
(e.g. data is expected to be already centered).
(i.e. data is expected to be centered).

normalize : boolean, optional, default False
This parameter is ignored when ``fit_intercept`` is set to False.
Expand Down
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