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Databricks Machine Learning Professional Exam - Topic 10 Question 54 Discussion

Which of the following is a reason for using Jensen-Shannon (JS) distance over a Kolmogorov-Smirnov (KS) test for numeric feature drift detection?
D) JS is more robust when working with large datasets
A) All of these reasons
B) JS is not normalized or smoothed
C) None of these reasons
E) JS does not require any manual threshold or cutoff determinations

Databricks Machine Learning Professional Exam - Topic 10 Question 54 Discussion

Actual exam question for Databricks's Databricks Machine Learning Professional exam
Question #: 54
Topic #: 10
[All Databricks Machine Learning Professional Questions]

Which of the following is a reason for using Jensen-Shannon (JS) distance over a Kolmogorov-Smirnov (KS) test for numeric feature drift detection?

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Suggested Answer: D

by Marion at May 11, 2026, 12:50 PM

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Christiane
24 days ago
I remember that JS distance is often preferred because it doesn't require manual thresholds, but I'm not sure if that's the only reason.
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