after reading some material i found few options for defining train and test sets:
- Just splitting with no change.
- Accumulating/Moving window of train set.
- leave a relatively small (warming) period between test and train sets and then use window again (including the warming period).
What should be the most accurate way for applying Machine Learning algorithms and parameters estimation. Thanks in advance!