Comments (2)
Hi @ihadanny, sorry for the rather late reply. in reply to your questions:
1: I here use observed values for the weather variables, but in the context of e.g. a full predictive model which would aim at predicting the cyclist numbers a few days in advance, you simply would use the outputs of a numerical weather prediction model
2: because of the nature of the model, you cannot really do cross validation, as you need to respect the chronological ordering of the time-series. Not sure about your comment related to an overfit, the model does not 'see' the test data at any point, and the train vs test validation metrics are quite similar
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