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Group duplicate shipment records before creating training: What control directly addresses this evaluation

AIGP Understanding How to Govern AI Development Medium

Duplicate or related shipment records must be grouped before splitting, preventing information leakage into held-out evaluation.

The question

A logistics scheduler is tested using records randomly split by row. The same shipment appears twice because one record reflects an update, and its duplicate landed in the held-out set. What control directly addresses this evaluation problem?

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  1. Tune the scheduler threshold using the current held-out predictions.
    Threshold tuning cannot repair information leakage because duplicate shipment information has already crossed the evaluation boundary.
  2. Increase the held-out sample size without changing the split procedure.
    A larger random split can still place related records across partitions, preserving leakage and overstating held-out performance.
  3. Add a second random test split to confirm the reported scheduling accuracy.
    Repeated random splitting can reproduce the same duplication problem unless related records are grouped first.
  4. Group duplicate shipment records before creating training and held-out partitions.
    Grouping related records before splitting keeps duplicate information within one partition and protects the independence of evaluation.
The trap
Choose the split unit based on independent real-world entities, not automatically on individual rows.

How to remember it

Duplicate or related shipment records must be grouped before splitting, preventing information leakage into held-out evaluation.

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