Hi All- (
@IngoRM,
@yyhuang,
@varunm1,
@hughesfleming68,
@tftemme,
@mschmitz,
@lionelderkrikor )
Say you had a model whose testing performance on timeseries data changed as you changed the length of the training period. A model trained with one particular training period length, however, was not consistently the top performer... On the same test sets, sometimes the model with 2 years of training performed best, sometimes the one with 1 year, or 18mos, etc.
I want to train a meta model that will choose which training period length-model to apply to the test set at any given time.
I looked at using the stacking operator, but, situated inside the validation process, varying length training periods won't work.
Can someone please suggest an alternate methodology (including meta model type)?
Thank you!
-Noel