Hello i am follow the time series forecasting tutorial in tensorflow https://www.tensorflow.org/tutorials/structured_data/time_series, I have the same project, the only difference is that I am using a different dataset, when evaluating the models, the model.evaluate () method returns an empty list, it does not return a value. When the model is trained with the fit() method, evaluation values are generated in
Tag: forecasting
auto.arima() equivalent for python
I am trying to predict weekly sales using ARMA ARIMA models. I could not find a function for tuning the order(p,d,q) in statsmodels. Currently R has a function forecast::auto.arima() which will tune the (p,d,q) parameters. How do I go about choosing the right order for my model? Are there any libraries available in python for this purpose? Answer You can