From d2d10bffde9a4d9c4b504d43575a6da6026df70f Mon Sep 17 00:00:00 2001 From: Gael Varoquaux Date: Tue, 13 Dec 2016 15:10:16 +0100 Subject: [PATCH] DOC: Fix the documentation of scoring LogisticCV --- sklearn/linear_model/logistic.py | 11 +++++++---- 1 file changed, 7 insertions(+), 4 deletions(-) diff --git a/sklearn/linear_model/logistic.py b/sklearn/linear_model/logistic.py index ac4973f1dfebf..1f0591ddcf24a 100644 --- a/sklearn/linear_model/logistic.py +++ b/sklearn/linear_model/logistic.py @@ -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.