From 394da108dd9a7d7d4304d88b8fe94f8b66e7a8c2 Mon Sep 17 00:00:00 2001 From: Jaymin Mistry Date: Sun, 8 Dec 2019 17:32:31 +0000 Subject: [PATCH] update _alpha_grid class in _coordinate_descent.py --- sklearn/linear_model/_coordinate_descent.py | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) diff --git a/sklearn/linear_model/_coordinate_descent.py b/sklearn/linear_model/_coordinate_descent.py index efe5612845157..30ccb0c9f702f 100644 --- a/sklearn/linear_model/_coordinate_descent.py +++ b/sklearn/linear_model/_coordinate_descent.py @@ -43,26 +43,26 @@ def _alpha_grid(X, y, Xy=None, l1_ratio=1.0, fit_intercept=True, y : ndarray, shape (n_samples,) Target values - Xy : array-like, optional + Xy : array-like, default=None Xy = np.dot(X.T, y) that can be precomputed. - l1_ratio : float + l1_ratio : float, default=1.0 The elastic net mixing parameter, with ``0 < l1_ratio <= 1``. For ``l1_ratio = 0`` the penalty is an L2 penalty. (currently not supported) ``For l1_ratio = 1`` it is an L1 penalty. For ``0 < l1_ratio <1``, the penalty is a combination of L1 and L2. - eps : float, optional + eps : float, default=1e-3 Length of the path. ``eps=1e-3`` means that ``alpha_min / alpha_max = 1e-3`` - n_alphas : int, optional + n_alphas : int, default=100 Number of alphas along the regularization path - fit_intercept : boolean, default True + fit_intercept : boolean, default=True Whether to fit an intercept or not - normalize : boolean, optional, default False + normalize : boolean, default=False This parameter is ignored when ``fit_intercept`` is set to False. If True, the regressors X will be normalized before regression by subtracting the mean and dividing by the l2-norm. @@ -70,7 +70,7 @@ def _alpha_grid(X, y, Xy=None, l1_ratio=1.0, fit_intercept=True, :class:`sklearn.preprocessing.StandardScaler` before calling ``fit`` on an estimator with ``normalize=False``. - copy_X : boolean, optional, default True + copy_X : boolean, optional, default=True If ``True``, X will be copied; else, it may be overwritten. """ if l1_ratio == 0: