Does anyone know what maybe the issue here? I couldn’t show the data due to confidentiality but all the static features are numeric and only id, date, y are left.

hey @Dihong Huang! Thanks for using mlforecast.I saw that you’re passing a set to the

target_transforms

argument. Could you try using a list? (

target_transforms=[Differences([1, 3, 6, 9])]

instead of

target_transforms={Differences([1, 3, 6, 9])}

)

Thank you! This solves my problem. Also, I wonder if mlforecast supports feature importances when using xgboost and random forest?

hey @Dihong Huang! cool. Yes, that’s possible. Once the models are fitted, you can access them through the

model_

attribute. And then you can retrieve the feature importance of the features using something like the following: