Databricks-Machine-Learning-Professional Exam Dumps | A Data Scientist needs to analyze drift detection results from Databricks Lakehouse Monitoring. The system

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Question 69/96

A Data Scientist needs to analyze drift detection results from Databricks Lakehouse Monitoring.
The system has generated both profile metrics and drift metrics tables. The scientist needs to identify baseline drift in numerical features by comparing current data against a baseline from 6 months ago. Which combination of table columns and values indicates baseline drift in a numerical feature?

A. window_cmp pointing to baseline time window and tv_distance > 0.5 with any drift_type value.

B. drift_type = "BASELINE", chi_squared_test.p_value < 0.05, and js_distance > 0.2.

C. drift_type = "BASELINE", ks_test.p_value < 0.05, and wasserstein_distance > 0.1.

D. log_type = "BASELINE" in profile metrics table with population_stability_index > 0.2 in drift metrics table.

Question 69/96

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