I was reading about cross validation equivalents for time series data and found a variation called blocked cross validation. On the page I was reading it says the following:
"However, this may introduce leakage from future data to the model. The model will observe future patterns to forecast and try to memorize them. That’s why blocked cross-validation was introduced.(...) The second (margin) is between the folds used at each iteration in order to prevent the model from memorizing patterns from an iteration to the next."
From my understanding, iterations are independent, thus, the model is learned from scratch in each iteration. How can the model "memorize" patterns from one iteration to the next?
The first graph represents the problematic approach and the second represents the blocked cross validation solution.