Brian Head10/16/2023, 3:21 PM
I get a warning message for some of the algos (e.g., LSTM, RNN) that the in sample preds may not be accurate due to the scaler (e.g.,
). Is this message still accurate? Does it only apply to RNN-based models (that's what it looks like from what I'm seeing in the warnings)?
WARNING: Predict insample might not provide accurate predictions for recurrent model LSTM class yet due to scaling.
Cristian (Nixtla)10/17/2023, 3:33 PM
to scale the data, and only for RNN methods. It will still return values, but we have seen that because of the way we are scaling, we have seen some performance degradation for the predict insample. If you scale the time series before (with the core class, see this tutorial: https://nixtla.github.io/neuralforecast/examples/time_series_scaling.html ) then this warning does not apply.
Brian Head10/18/2023, 2:16 PM
. I started getting an error
after making the scaling change. It still happens after switching back to what I had. I can't find anything else I've changed. Any ideas?
ValueError: could not broadcast input array from shape (48384,9) into shape (48222,9)
both work as expected. It's only a problem with the