Add parameter to train_test_split for deterministic splitting and tests #31097
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Why not use Also it does not seem right to do (hash mod 10^8) and divide the hashed array by the max value |
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Reference Issues/PRs
Fixes #30992
See also the discussion in #30992.
What does this implement/fix? Explain your changes.
This PR adds a new
uidparameter tosklearn.model_selection.train_test_split, allowing for deterministic splitting of datasets using unique identifiers. This ensures that samples with the same UID are always assigned to the same split (train or test), regardless of dataset order. It helps with stability and reproducibility, especially in production environments or pipelines where data might be reshuffled.Key details:
uidargument (mutually exclusive withstratifyandshuffle=False)Any other comments?
Let me know if there are naming or API design considerations you'd like improved — happy to adjust the implementation. Thanks!