DOC Add objective function in `Lasso` docstrings for target matrix
@@ -1206,7 +1206,17 @@ class Lasso(ElasticNet):
that maximum coordinate update, i.e. :math:`\\max_j |w_j^{new} - w_j^{old}|`
is smaller than `tol` times the maximum absolute coefficient, :math:`\\max_j |w_j|`.
If so, then additionally check whether the dual gap is smaller than `tol` times
- :math:`||y||_2^2 / n_{\text{samples}}`.
+ :math:`||y||_2^2 / n_{\\text{samples}}`.
+
+ The target can be a 2-dimensional array, resulting in the optimization of the
+ following objective::
+
+ (1 / (2 * n_samples)) * ||Y - XW||^2_F + alpha * ||W||_11
+
+ where :math:`||W||_{1,1}` is the sum of the magnitude of the matrix coefficients.
+ It should not be confused with :class:`~sklearn.linear_model.MultiTaskLasso` which
+ instead penalizes the :math:`L_{2,1}` norm of the coefficients, yielding row-wise
+ sparsity in the coefficients.
Examples
--------
