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What cross validation technique would you use on time series data set? Is it k-fold or LOOCV?
in Data Science by Diamond (49,859 points) | 7 views

1 Answer

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I would use any of the two methods because a time series is sequential in a chronological manner.

In time series problems, k fold is not ideal because there might be some pattern in year 4 or 5 which is not in year 3. Resampling the data set will separate these trends, and we might end up validation on past years, which is incorrect. Instead, we can use forward chaining strategy with 5 fold as shown below:

  • 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]

where 1,2,3,4,5,6 represents “year”.

by Wooden (3,215 points)

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