[MRG] FIX lasso/elasticnet example did not add noise to simulated data.
The first argument of np.random.normal is the mean of the distribution, and
not the output shape. The example thus did not add noise but only an intercept
to the model.
@@ -28,7 +28,7 @@ coef[inds[10:]] = 0 # sparsify coef
y = np.dot(X, coef)
# add noise
-y += 0.01 * np.random.normal((n_samples,))
+y += 0.01 * np.random.normal(size=n_samples)
# Split data in train set and test set
n_samples = X.shape[0]
