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The .fit method uses ALL the data available to train the models. Horizon 0 raises an error because it means that nothing should be forecasted. If you want to evaluate the accuracy of your forecast you can manually split the data. Something like

Y_df = AirPassengersDF.copy()
mean = Y_df[Y_df.ds<='1959-12-31']['y'].mean()
std = Y_df[Y_df.ds<='1959-12-31']['y'].std()

Y_train_df = Y_df[Y_df.ds<='1959-12-31'] # 132 train
Y_test_df = Y_df[Y_df.ds>'1959-12-31']   # 12 test

However, we rather recommend using the the crossvalidation function to evaluate perfomance across different windowos. BTW: this should be in #C031M8RLC66

i know when make the horizan 0 it means no things to forecasting but i guess i didn't explain my question in good way