What cross-validation technique would you use on a time series dataset?

Data Science, AI and ML
#1

Instead of using standard k-folds cross-validation, you have to pay attention to the fact that a time series is not randomly distributed data—it is inherently ordered by chronological order. If a pattern emerges in later time periods, for example, your model may still pick up on it even if that effect doesn’t hold in earlier years!

You’ll want to do something like forward chaining where you’ll be able to model on past data then look at forward-facing data.

  • Fold 1 : training [1], test [2]
  • Fold 2 : training [1 2], test [3]
  • Fold 3 : training [1 2 3], test [4]
  • Fold 4 : training [1 2 3 4], test [5]
  • Fold 5 : training [1 2 3 4 5], test [6]