We should add repeated k-fold cross-validation. It's something a lot of people use, and it's tricky to implement in scikit-learn. In particular with the recent changes to cross-validation,

cv = KFold(shuffle=True)
results = []
for i in range(10):
    results.append(cross_val_score(est, X, y, cv=cv))

yields repeated cross-validation in 0.17 and 0.18, but not in 0.18.1 or dev (I think?)

We could do this with a wrapper that sets the random_state or we could explicitly write RepeatedKFold and RepeatedStratifiedKFold.