Cuestionario vinculado a una guía · Medio Nivel

Prueba de puertas de validación del modelo antes de la implementación

Diseñe criterios de validación previos al despliegue que combinen calidad de la evidencia, análisis de subgrupos, verificaciones operativas y controles de implementación por etapas.

Rutas de guía relacionadasPuertas de validación del modelo antes de la implementación
Pregunta 1 de 8

Why define model gate thresholds before reviewing candidate results?

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Las respuestas y explicaciones aparecen a medida que realiza el cuestionario.

  1. Why define model gate thresholds before reviewing candidate results?
    • It reduces the risk of selecting criteria after seeing which ones the model passes
    • It allows acceptance thresholds to be changed after reviewing results
    • It makes small subgroup estimates precise by definition
    • It removes the need to compare against any baseline
  2. A subgroup metric is based on very few examples. How should a gate treat it?
    • As a certain pass if its point estimate is high
    • As uncertain or inconclusive under a predefined sample rule
    • As proof the subgroup does not matter
    • As equal evidence to a large sample automatically
  3. What does a canary deployment add after offline validation?
    • A replacement for model quality metrics
    • Proof that offline data were representative
    • A limited live exposure with monitoring and rollback criteria
    • A guarantee no user will be affected
  4. Which check is a technical hard blocker rather than a statistical quality threshold?
    • The baseline has a slightly lower metric
    • The confidence interval is close to a target
    • A subgroup estimate is noisy
    • The artifact signature fails verification
  5. Why compare a candidate with the deployed model and a baseline?
    • To guarantee better performance on every future case
    • To determine whether it adds value or causes meaningful regression
    • To avoid defining evaluation data
    • To replace all slice checks
  6. What should a gate report retain for reproducibility?
    • The deployment password
    • Only a green status icon
    • Data version, candidate digest, metric definitions and thresholds
    • A model name without build identity
  7. What does passing a predeployment gate not certify?
    • A result on the reported evaluation data
    • Compliance with the specified release criteria
    • The exact artifact evaluated when its digest is recorded
    • Universal safety across all contexts and future populations
  8. Why verify that the deployed artifact matches the evaluated candidate?
    • Otherwise the release may run different bytes from those that passed the gate
    • It changes the validation threshold
    • It ensures fairness automatically
    • It increases the model's sample size