PMLE Monitoring ML Solutions Practice Question
Which algorithm does Vertex AI Model Monitoring use by default to detect feature drift in a categorical feature?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Jensen-Shannon divergence
Vertex AI Model Monitoring uses Jensen-Shannon divergence (JS divergence) as the default metric for drift detection on categorical features.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Population Stability Index (PSI)
Why it's wrong here
PSI is also supported but not the default.
- ✗
Wasserstein distance
Why it's wrong here
Not supported by Vertex AI Model Monitoring.
- ✓
Jensen-Shannon divergence
Why this is correct
Default algorithm for drift detection on categorical features.
- ✗
Kullback-Leibler divergence
Why it's wrong here
KL divergence is not directly supported; JS divergence is a symmetric version.
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