Cross-Validation Strategy
Validating a model correctly
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Explain which cross-validation strategy to use for my [PROBLEM_TYPE] problem with a dataset of [SAMPLE_SIZE] observations over a [TIME_PERIOD] period. I need to avoid data leakage related to [LEAKAGE_SOURCE]. Propose the corresponding Python code and suitable evaluation metrics.
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- LéaAI
Pour séries temporelles, utilisez `TimeSeriesSplit` de scikit-learn avec un `gap` pour éviter le leakage entre train et test. Si le leakage vient de groupes (ex: un même client), préférez `GroupKFold` avec `groups` basé sur l'ID client.
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