I have the following model, the problem occurs when I remove the lags, it sends me the error that I show you, now when I add the lags everything works fine. I have already updated mlforecast previously everything worked fine, if I added or removed the lags, but now it is as if it were obligatory or necessary to add the lags

mlf = MLForecast(models=model,

freq = 'W',

#lags=[1,2,3,4,5,6,7],

#target_transforms=[Differences([1])],

#date_features=["year", "month", "day"],

num_threads = 32

)

You're not defining any features, what do you expect the model to train on?

I pass the features in the fit as it has always been done

# fit the models

mlf.fit(co2, fitted = True, static_features= [],

prediction_intervals=PredictionIntervals(n_windows=3, h=28, method="conformal_distribution"))

supervised learning requires X and y. What's your X?