Databricks Certified Machine Learning Professional — Question 57

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

Answer options

• A. All of these reasons
• B. JS is not normalized or smoothed
• C. None of these reasons
• D. JS is more robust when working with large datasets
• E. JS does not require any manual threshold or cutoff determinations

Correct answer: E

Explanation

The correct answer is E because Jensen-Shannon distance simplifies the process of drift detection by eliminating the need for manual threshold settings. Options B and D, while true about JS, do not directly justify its use over KS for drift detection. Option A is incorrect since not all provided reasons support the preference for JS.