What is cross-validation techniques would you be using on a time series dataset?

Cross-validation is used for tuning the hyperparameters and producing measurements of model performance. With the time series data, we can’t use the traditional cross-validation technique due to two main reasons which are as follows -

  • Temporal dependencies
  • Arbitrary Choice of Test Set

For time-series data, we use nested cross-validation that provides an almost unbiased estimate of the true error. A nested CV consists of an inner loop for parameter tuning and an outer loop for error estimation.