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Blocked time series cross-validation is very much like traditional cross-validation. As you know CV, takes a portion of the dataset and sets it aside only for testing purposes. The data can be taken from any part of the original data, beginning, middle, end, etc. It does not matter where because you assume the variance is the same throughout. But since the time series data IS changing in some ...
time series - What is and why use blocked cross-validation? - Data ...
1- Why most CNN models don't use Cross Validation? 2- If I use Cross Validation, how can I generate the confusion matrix? Can I split dataset to train/test and then do cross validation on train set as train/validation (i.e., doing cross validation as train/validation except for the usual train/test) and at last use test set the same way? Or how?