Non-R Looping to augment training dataset with latest data RRS feed

  • Question

  • I have a historical dataset for forecasting for which i want to do "honest" cross-validation - in the sense of always forecasting forward in time (rather than randomly sampling for CV).  I have limited data (say, n=200), and a short forecast horizon (say, k=5).

    for example, here is what I'd like to do without having to use R:

    1. Train on the first 100, and CV using the next 5

    2. Train on the first 105 (OR slide the window, and train on rows 6-105), and CV using the next 5 


    Is there any way to do this easily and efficiently within Azure - i.e., without massively duplicating code or data?

    David E. Coleman, Mgr. Decision Analytics, Alcoa, Pittsburgh, PA, USA

    Thursday, June 16, 2016 8:32 PM