mathurinm

Yes it's benchopt's make_correlated_data : https://benchopt.github.io/generated/benchopt.datasets.simulated.make_correlated_data.html#benchopt.datasets.simulated.make_correlated_data

Approximately, benchopt's density is 0.2 so w_true has 1_000 nnz I just pushed https://github.com/mathurinm/andersoncd/blob/master/andersoncd/tests/benchmark.py to play faster with the code, so far we are never faster than sklearn while celer...

@QB3 I have edited the todolist for monday's sprint, feel free to add stuff. I think having a functional enet at the end of the day would be nice and...

it seems that you added rcv1 to the examples so you need to update the cache key (if you read the outputs of the examples, rcv1 is being freshly downloaded)

ah... that's bad because correctness would make the access harder to me

Given the past work, I think it should be doable to have something along the lines of: ``` criterion = HeldOutMSE(idx_train, idx_val) # better yet, train_frac=0.75 if possible with CV...

and put LassoCV test, too ?

@RomainBrault what is the status on this?