The best time series prediction model is often “Use the previous day (or week’s) value”. The best classification model is often “pretend everything is the same.

The best time series prediction model is often “Use the previous day (or week’s) value”. The best classification model is often “pretend everything is the same.” The best regression model is often “assume it’s the mean”. This should not be surprising: a core premise of data science (empiricism in general? All logic and human knowledge?) is that intuition is often wrong. Initial hypotheses/problem definitions are just intuition.