DOC correct behavior of precompute with sparse input
@@ -615,7 +615,7 @@ class ElasticNet(MultiOutputMixin, RegressorMixin, LinearModel):
default=False
Whether to use a precomputed Gram matrix to speed up
calculations. The Gram matrix can also be passed as argument.
- For sparse input this option is always ``True`` to preserve sparsity.
+ For sparse input this option is always ``False`` to preserve sparsity.
max_iter : int, default=1000
The maximum number of iterations.
@@ -944,7 +944,7 @@ class Lasso(ElasticNet):
Whether to use a precomputed Gram matrix to speed up
calculations. If set to ``'auto'`` let us decide. The Gram
matrix can also be passed as argument. For sparse input
- this option is always ``True`` to preserve sparsity.
+ this option is always ``False`` to preserve sparsity.
copy_X : bool, default=True
If ``True``, X will be copied; else, it may be overwritten.
