@@ -69,7 +69,7 @@ def lars_path(
6969 y : None or array-like of shape (n_samples,)
7070 Input targets.
7171
72- Xy : array-like of shape (n_samples ,) or (n_samples , n_targets), \
72+ Xy : array-like of shape (n_features ,) or (n_features , n_targets), \
7373 default=None
7474 `Xy = np.dot(X.T, y)` that can be precomputed. It is useful
7575 only when the Gram matrix is precomputed.
@@ -215,7 +215,7 @@ def lars_path_gram(
215215
216216 Parameters
217217 ----------
218- Xy : array-like of shape (n_samples ,) or (n_samples , n_targets)
218+ Xy : array-like of shape (n_features ,) or (n_features , n_targets)
219219 Xy = np.dot(X.T, y).
220220
221221 Gram : array-like of shape (n_features, n_features)
@@ -362,7 +362,7 @@ def _lars_path_solver(
362362 y : None or ndarray of shape (n_samples,)
363363 Input targets.
364364
365- Xy : array-like of shape (n_samples ,) or (n_samples , n_targets), \
365+ Xy : array-like of shape (n_features ,) or (n_features , n_targets), \
366366 default=None
367367 `Xy = np.dot(X.T, y)` that can be precomputed. It is useful
368368 only when the Gram matrix is precomputed.
@@ -1110,7 +1110,7 @@ def fit(self, X, y, Xy=None):
11101110 y : array-like of shape (n_samples,) or (n_samples, n_targets)
11111111 Target values.
11121112
1113- Xy : array-like of shape (n_samples ,) or (n_samples , n_targets), \
1113+ Xy : array-like of shape (n_features ,) or (n_features , n_targets), \
11141114 default=None
11151115 Xy = np.dot(X.T, y) that can be precomputed. It is useful
11161116 only when the Gram matrix is precomputed.
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