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Applied ML

Your experiment decision record

Write this before opening the test. Replace every prompt with your own reasoning.

  1. Row unit, prediction time, action and person responsible for reviewing alerts:
  2. Regression and classification label definitions and availability horizon:
  3. Features allowed and forbidden, with two availability examples:
  4. Exact split windows, gaps and why random/group splits answer different questions:
  5. Baselines, primary metrics and proposed operational cost assumptions:
  6. Candidate models, training-only tuning search and selection rule:
  7. Calibration policy and threshold selection window, including capacity constraint:
  8. Validation results with sample sizes and uncertainty/limitations:
  9. Freeze identifier and date; what changes would require a new evaluation:
  10. After freeze only: final test results and baseline comparison, including capacity:
  11. Error investigation and what cannot be inferred causally:
  12. Handoff owner, monitoring signals, matured-label schedule, fallback and go/no-go:

Do not write that the system is production-ready merely because code runs.

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