[MRG] Added missing sag_solver documentation
@@ -131,7 +131,13 @@ def sag_solver(X, y, sample_weight=None, loss='log', alpha=1., beta=0.,
*loss='multinomial'*
alpha : float, optional
- Constant that multiplies the regularization term. Defaults to 1.
+ L2 regularization term in the objective function
+ ``(0.5 * alpha * || W ||_F^2)``. Defaults to 1.
+
+ beta : float, optional
+ L1 regularization term in the objective function
+ ``(beta * || W ||_1)``. Only applied if ``is_saga`` is set to True.
+ Defaults to 0.
max_iter : int, optional
The max number of passes over the training data if the stopping
