OLA interview Question | Cross Validation Technique
Question
What cross-validation technique would you use on a time series dataset?
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In time series split, we cant shuffle that makes it different from normal cross-validation techniques
So, we need a special cross-validation technique which we can import from sklearn.model_selection
Time Series cross-validator
Provides train/test indices to split time series data samples that are observed at fixed time intervals, in train/test sets. In each split, test indices must be higher than before, and thus shuffling in cross validator is inappropriate.
This cross-validation object is a variation of KFold. In the kth split, it returns first k folds as train set and the (k+1)th fold as test set.
Note that unlike standard cross-validation methods, successive training sets are supersets of those that come before them.