Do we need to tune same model differently for different window sizes in time series data classification?
In my opinion it should be tuned again.
Reasoning:
Using different window size is almost equivalent to using different features(as in a non time-series modeling). Tuning hyper-parameters is usually done after features were selected(I.E for a given set of features).