For time series datasets, k fold can be troublesome because there might be some pattern in year 4 or 5 which is not in year 3. Resampling the dataset 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 cross validation 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”. For this, the assumption is to have 6 years of historical data available.