From 91de1c2a9d5268e045db3dd67bf036ef4d7e98d9 Mon Sep 17 00:00:00 2001 From: Paolo Losi Date: Mon, 11 Apr 2011 22:04:53 +0200 Subject: [PATCH] review of min_C doc strings --- scikits/learn/linear_model/logistic.py | 14 ++++++++++++++ scikits/learn/linear_model/sparse/logistic.py | 14 ++++++++++++++ 2 files changed, 28 insertions(+) diff --git a/scikits/learn/linear_model/logistic.py b/scikits/learn/linear_model/logistic.py index 19b84f526c2..06ef3c10fd1 100644 --- a/scikits/learn/linear_model/logistic.py +++ b/scikits/learn/linear_model/logistic.py @@ -130,6 +130,20 @@ class LogisticRegression(BaseLibLinear, ClassifierMixin, if C is greater that min_C there is at least one non-zero coefficient. This value is valid if class_weight parameter in fit() is not set. + + Parameters + ---------- + X : array-like, shape = [n_samples, n_features] + Training vector, where n_samples in the number of samples and + n_features is the number of features. + + y : array-like, shape = [n_samples] + Target vector relative to X + + Returns + ------- + min_C: float + minimum value for C """ if self.penalty != 'l1': raise ValueError('penalty is not l1') diff --git a/scikits/learn/linear_model/sparse/logistic.py b/scikits/learn/linear_model/sparse/logistic.py index 189f7a095b0..4f5af3ca809 100644 --- a/scikits/learn/linear_model/sparse/logistic.py +++ b/scikits/learn/linear_model/sparse/logistic.py @@ -119,6 +119,20 @@ class LogisticRegression(SparseBaseLibLinear, ClassifierMixin, if C is greater that min_C there is at least one non-zero coefficient. This value is valid if class_weight parameter in fit() is not set. + + Parameters + ---------- + X : sparse matrix, shape = [n_samples, n_features] + Training vector, where n_samples in the number of samples and + n_features is the number of features. + + y : array, shape = [n_samples] + Target vector relative to X + + Returns + ------- + min_C: float + minimum value for C """ if self.penalty != 'l1': raise ValueError('penalty is not l1')