I created a predicative model using neural networks and applied in on a time series. This is how I split my data:
train: 1, 2, 3, 4, 5, 6 -> 7, 8
test: 3, 4, 5, 6, 7, 8 -> 9, 10
The answer Using k-fold cross-validation for time-series model selection provides a similar solution to mine although I skip the initial part of the time series in the test data.
However, according to an answer in another question:
Leakage is when your test data is, in some form, also part of your train data.
If the k-fold validation used data from the training set in the test set how does it not induce data leakage?