[D] Generalization in time-series data and the underlying assumptions of ML models.

I've been refreshing some of my groundwork theoretical knowledge on statistics and generalization; So basically all "classical" statistical models assume that the data the model would be predicting comes from the same distribution as the data the model was trained on. This in turn gives us concrete figures on the generalization of our model.

But what about time-series? Time-series datasets are inherently not drawn from the same distribution. So I suppose this means I can't have figures on generalization? How …

data machinelearning ml ml models time