Qu'est-ce que « Adversarial validation, leakage audit » ?

Adversarial validation trains a classifier to tell training rows from test rows; an AUC well above one half means the features locate the split, so shuffled folds will leak and the test period differs from the training period. A leakage audit is the set of checks a pipeline passes before its score is believed: at least a truncation test of every feature, a canary run of the whole pipeline, a fold-overlap check of the splits, and adversarial validation.