8000 [MRG+1] DOC: Fix the documentation of scoring LogisticCV by GaelVaroquaux · Pull Request #8099 · scikit-learn/scikit-learn · GitHub
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[MRG+1] DOC: Fix the documentation of scoring LogisticCV #8099

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Dec 22, 2016
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[MRG+1] DOC: Fix the documentation of scoring LogisticCV #8099

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11 changes: 7 additions & 4 deletions sklearn/linear_model/logistic.py
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Expand Up @@ -1368,10 +1368,13 @@ class LogisticRegressionCV(LogisticRegression, BaseEstimator,
l2 penalty with liblinear solver. Prefer dual=False when
n_samples > n_features.

scoring : callabale
Scoring function to use as cross-validation criteria. For a list of
scoring functions that can be used, look at :mod:`sklearn.metrics`.
The default scoring option used is accuracy_score.
scoring : string, callable, or None
A string (see model evaluation documentation) or
a scorer callable object / function with signature
``scorer(estimator, X, y)``. For a list of scoring functions
that can be used, look at :mod:`sklearn.metrics`. The
default scoring option used is accuracy_score.


solver : {'newton-cg', 'lbfgs', 'liblinear', 'sag'}
Algorithm to use in the optimization problem.
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