FA-100342 / Feature preprocessing fit scope / Member archive

Mean imputation uses held-out rows while fitting · case 02

Mean imputation uses held-out rows while fitting.

Member previewVariant 2 · 3 implementations · 7 checks per implementation

Case contract

Train and transform are row lists of one numeric feature with None missing. Fit the arithmetic mean of observed training values (0 when none); replace transform missing values only.

Why this case matters

A small deterministic preprocessing contract makes the fit boundary and transform behavior directly inspectable.

One recorded failure

Sample boundary fixture

This sample comes from the broken implementation of a controlled reproducer.

Boundary fixture	Actual	Expected	Outcome
two gaps	`[[5.0, 4], [6, 5.0]]`	`[[4, 4], [6, 4]]`	Failed

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This record includes three runnable implementations, regression fixtures, execution results, and source hashes.

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