DATABRICKS-MLP Question 49

Community Discussion

Written by other learners. Comments can disagree with the marked answer — check the official documentation when in doubt.

• Chose A0

  - Correct answer : A — A representative sample of the training or validation data whose distribution reflects what the model was built to expect. A . A baseline built from the training or validation distribution gives drift metrics a stable, meaningful reference point representing what the model expects, which is what current production data is compared against. B . Unprocessed raw traffic from before any cleaning does not represent the distribution the model was trained and validated on, so comparisons against it would flag differences that have nothing to do with real drift. C . A synthetic dataset covering unlikely feature combinations skews the baseline away from realistic production behavior, making drift statistics measure divergence from an artificial reference rather than the model's actual training assumptions. D . Continuously refreshing the baseline from the live table eliminates any fixed reference point, so drift can never be detected because the baseline would always move in lockstep with the data being compared.