Fix doc Multitasks
@@ -1611,7 +1611,8 @@ class MultiTaskElasticNet(Lasso):
coef_ : array, shape (n_tasks, n_features)
Parameter vector (W in the cost function formula). If a 1D y is \
- passed in at fit (non multi-task usage), ``coef_`` is then a 1D array
+ passed in at fit (non multi-task usage), ``coef_`` is then a 1D array.
+ Note that ``coef_`` stores the transpose of ``W``, ``W.T``.
n_iter_ : int
number of iterations run by the coordinate descent solver to reach
@@ -1792,7 +1793,8 @@ class MultiTaskLasso(MultiTaskElasticNet):
Attributes
----------
coef_ : array, shape (n_tasks, n_features)
- parameter vector (W in the cost function formula)
+ Parameter vector (W in the cost function formula).
+ Note that ``coef_`` stores the transpose of ``W``, ``W.T``.
intercept_ : array, shape (n_tasks,)
independent term in decision function.
@@ -1950,6 +1952,7 @@ class MultiTaskElasticNetCV(LinearModelCV, RegressorMixin):
coef_ : array, shape (n_tasks, n_features)
Parameter vector (W in the cost function formula).
+ Note that ``coef_`` stores the transpose of ``W``, ``W.T``.
alpha_ : float
The amount of penalization chosen by cross validation
@@ -2115,6 +2118,7 @@ class MultiTaskLassoCV(LinearModelCV, RegressorMixin):
coef_ : array, shape (n_tasks, n_features)
Parameter vector (W in the cost function formula).
+ Note that ``coef_`` stores the transpose of ``W``, ``W.T``.
alpha_ : float
The amount of penalization chosen by cross validation
