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About the weighted Lasso example, it seems you are using kfold for training sparse-ho crossval function, then why are you passing indices in heldout function line 80? It should be HeldOutMSE(None, None)?
It would be nice when you are splitting to have X_train y_test instead of passing again X and y. I have noticed that the number of training samples could be too small. As you can see if we have more samples, sparse-ho is doing better....
The text was updated successfully, but these errors were encountered:
Hi @QB3 @mathurinm
About the weighted Lasso example, it seems you are using kfold for training sparse-ho crossval function, then why are you passing indices in heldout function line 80? It should be HeldOutMSE(None, None)?
It would be nice when you are splitting to have X_train y_test instead of passing again X and y. I have noticed that the number of training samples could be too small. As you can see if we have more samples, sparse-ho is doing better....
The text was updated successfully, but these errors were encountered: