Databricks
CERTIFIED-MACHINE-LEARNING-PROFESSIONAL · Question #45
Which of the following is a reason for using Jensen-Shannon (JS) distance over a Kolmogorov- Smirnov (KS) test for numeric feature drift detection?
Sign in or unlock CERTIFIED-MACHINE-LEARNING-PROFESSIONAL to reveal the answer and full explanation for question #45. The question stem and answer options stay visible for context.
Question
Which of the following is a reason for using Jensen-Shannon (JS) distance over a Kolmogorov- Smirnov (KS) test for numeric feature drift detection?
Options
- AAll of these reasons
- BJS is not normalized or smoothed
- CNone of these reasons
- DJS is more robust when working with large datasets
- EJS does not require any manual threshold or cutoff determinations
Unlock CERTIFIED-MACHINE-LEARNING-PROFESSIONAL to see the answer
You've previewed enough free CERTIFIED-MACHINE-LEARNING-PROFESSIONAL questions. Unlock CERTIFIED-MACHINE-LEARNING-PROFESSIONAL for full answers, explanations, the timed quiz mode, progress tracking, and the master PDF. Question stem and options stay visible so you can still see what's on the exam.