From Mystery Returns to a Real Prediction Target

Same returns project, one week apart. What changed? Before: a pile of cases and a vague request After: a labeled prediction target plus an exploration lane The target changed from vague bad product to refund approved within seven days, so training has an answer column instead of a subjective wish. The feature list changed to intake-time fields only, because inference must use information available before the refund decision. Clustering stayed in the workflow as exploration, because unsupervised groups can suggest defect themes but should not be treated as refund labels. The model job became measurable only after the team separated…

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