Exam MLA-C01 Topic 2 Question 69 Discussion
Actual exam question for Amazon's MLA-C01 exam
Question #: 69
Topic #: 2
Question #: 69
Topic #: 2
An ML engineer is using Amazon Quick Suite (previously known as Amazon QuickSight) anomaly detection to detect very high or very low machine operating temperatures compared to normal. The ML engineer sets the Severity parameter to Low and above. The ML engineer sets the Direction parameter to All.
What effect will the ML engineer observe in the anomaly detection results if the ML engineer changes the Direction parameter to Lower than expected?
What effect will the ML engineer observe in the anomaly detection results if the ML engineer changes the Direction parameter to Lower than expected?
Suggested Answer: B Vote an answer
In Amazon QuickSight anomaly detection, the Direction parameter controls which deviations from the expected baseline are flagged as anomalies. When Direction is set to All, QuickSight detects both higher-than- expected and lower-than-expected values. This results in a larger set of detected anomalies, increasing recall.
When the Direction parameter is changed to Lower than expected, the anomaly detection algorithm filters out all higher-than-expected anomalies and only reports unusually low values. Because the scope of detection is narrowed, the total number of detected anomalies decreases. As a result, fewer true anomalies are identified overall, which reduces recall.
Since fewer data points are evaluated as potential anomalies, the frequency of anomaly identification also decreases. This behavior is consistent with AWS documentation, which explains that directional filtering limits detection to a subset of deviations and therefore reduces overall anomaly counts.
Therefore, changing the Direction from All to Lower than expected leads to decreased anomaly identification frequency and decreased recall.
When the Direction parameter is changed to Lower than expected, the anomaly detection algorithm filters out all higher-than-expected anomalies and only reports unusually low values. Because the scope of detection is narrowed, the total number of detected anomalies decreases. As a result, fewer true anomalies are identified overall, which reduces recall.
Since fewer data points are evaluated as potential anomalies, the frequency of anomaly identification also decreases. This behavior is consistent with AWS documentation, which explains that directional filtering limits detection to a subset of deviations and therefore reduces overall anomaly counts.
Therefore, changing the Direction from All to Lower than expected leads to decreased anomaly identification frequency and decreased recall.
by Edmund at Mar 26, 2026, 08:42 PM
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