Build a Leakage-Safe Preprocessing Flow
Apply split-fit-transform sequencing to prevent preprocessing leakage in a supervised modeling workflow.
A model pipeline performs imputation, scaling, and feature selection before creating train and validation splits. Leakage-safe sequence: split first, fit preprocessing on train, transform validation/test, then evaluate once. The common trap is treating preprocessing as harmless cleanup. If it learns statistics or choices from all rows, it can leak evaluation information. Split first Create train and validation sets using the same time or grouping logic that deployment will face. The split defines the boundary between learning data and evaluation data. Build it before learned transformations. Fit on train only Fit imputers, scalers, encoders, vectorizers, and feature selectors using only training…
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