Skip to content

[MRG+1] Fix LogisticRegression see also should include LogisticRegressiononCV #10022

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 1 commit into from
Oct 27, 2017
Merged

[MRG+1] Fix LogisticRegression see also should include LogisticRegressiononCV #10022

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
4 changes: 4 additions & 0 deletions sklearn/calibration.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -265,6 +265,10 @@ class _CalibratedClassifier(object):
if None, then classes is extracted from the given target values
in fit().

See also
--------
CalibratedClassifierCV

References
----------
.. [1] Obtaining calibrated probability estimates from decision trees
Expand Down
9 changes: 9 additions & 0 deletions sklearn/feature_selection/rfe.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -101,6 +101,11 @@ class RFE(BaseEstimator, MetaEstimatorMixin, SelectorMixin):
>>> selector.ranking_
array([1, 1, 1, 1, 1, 6, 4, 3, 2, 5])

See also
--------
RFECV : Recursive feature elimination with built-in cross-validated
selection of the best number of features

References
----------

Expand Down Expand Up @@ -365,6 +370,10 @@ class RFECV(RFE, MetaEstimatorMixin):
>>> selector.ranking_
array([1, 1, 1, 1, 1, 6, 4, 3, 2, 5])

See also
--------
RFE : Recursive feature elimination

References
----------

Expand Down
11 changes: 9 additions & 2 deletions sklearn/linear_model/coordinate_descent.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -640,6 +640,8 @@ class ElasticNet(LinearModel, RegressorMixin):

See also
--------
ElasticNetCV : Elastic net model with best model selection by
cross-validation.
SGDRegressor: implements elastic net regression with incremental training.
SGDClassifier: implements logistic regression with elastic net penalty
(``SGDClassifier(loss="log", penalty="elasticnet")``).
Expand Down Expand Up @@ -1688,7 +1690,10 @@ class MultiTaskElasticNet(Lasso):

See also
--------
ElasticNet, MultiTaskLasso
MultiTaskElasticNet : Multi-task L1/L2 ElasticNet with built-in
cross-validation.
ElasticNet
MultiTaskLasso

Notes
-----
Expand Down Expand Up @@ -1873,7 +1878,9 @@ class MultiTaskLasso(MultiTaskElasticNet):

See also
--------
Lasso, MultiTaskElasticNet
MultiTaskLasso : Multi-task L1/L2 Lasso with built-in cross-validation
Lasso
MultiTaskElasticNet

Notes
-----
Expand Down
1 change: 1 addition & 0 deletions sklearn/linear_model/least_angle.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -824,6 +824,7 @@ class LassoLars(Lars):
Lasso
LassoCV
LassoLarsCV
LassoLarsIC
sklearn.decomposition.sparse_encode

"""
Expand Down
1 change: 1 addition & 0 deletions sklearn/linear_model/logistic.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -1120,6 +1120,7 @@ class LogisticRegression(BaseEstimator, LinearClassifierMixin,
SGDClassifier : incrementally trained logistic regression (when given
the parameter ``loss="log"``).
sklearn.svm.LinearSVC : learns SVM models using the same algorithm.
LogisticRegressionCV : Logistic regression with built-in cross validation

Notes
-----
Expand Down
2 changes: 1 addition & 1 deletion sklearn/linear_model/omp.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -598,7 +598,7 @@ class OrthogonalMatchingPursuit(LinearModel, RegressorMixin):
Lars
LassoLars
decomposition.sparse_encode

OrthogonalMatchingPursuitCV
"""
def __init__(self, n_nonzero_coefs=None, tol=None, fit_intercept=True,
normalize=True, precompute='auto'):
Expand Down
20 changes: 12 additions & 8 deletions sklearn/linear_model/ridge.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -624,7 +624,10 @@ class Ridge(_BaseRidge, RegressorMixin):

See also
--------
RidgeClassifier, RidgeCV, :class:`sklearn.kernel_ridge.KernelRidge`
RidgeClassifier : Ridge classifier
RidgeCV : Ridge regression with built-in cross validation
:class:`sklearn.kernel_ridge.KernelRidge` : Kernel ridge regression
Copy link
Member

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Why do you use such syntax here?
What about just kernel_ridge.KernelRidge?

Copy link
Member

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Note it was already like that before and the link works properly (I checked at some point I think). I am not sure but maybe this is to ensure there is a proper link in the doc. Wild guess: maybe the link is found automatically if the name is in the same module, but maybe not if it's another subpackage.

combines ridge regression with the kernel trick

Examples
--------
Expand Down Expand Up @@ -770,7 +773,8 @@ class RidgeClassifier(LinearClassifierMixin, _BaseRidge):

See also
--------
Ridge, RidgeClassifierCV
Ridge : Ridge regression
RidgeClassifierCV : Ridge classifier with built-in cross validation

Notes
-----
Expand Down Expand Up @@ -1233,9 +1237,9 @@ class RidgeCV(_BaseRidgeCV, RegressorMixin):

See also
--------
Ridge: Ridge regression
RidgeClassifier: Ridge classifier
RidgeClassifierCV: Ridge classifier with built-in cross validation
Ridge : Ridge regression
RidgeClassifier : Ridge classifier
RidgeClassifierCV : Ridge classifier with built-in cross validation
"""
pass

Expand Down Expand Up @@ -1318,9 +1322,9 @@ class RidgeClassifierCV(LinearClassifierMixin, _BaseRidgeCV):

See also
--------
Ridge: Ridge regression
RidgeClassifier: Ridge classifier
RidgeCV: Ridge regression with built-in cross validation
Ridge : Ridge regression
RidgeClassifier : Ridge classifier
RidgeCV : Ridge regression with built-in cross validation

Notes
-----
Expand Down