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AAIA · Question #73
AAIA Question #73: Real Exam Question with Answer & Explanation
The correct answer is C: K-means clustering algorithms are significantly sensitive to outliers and dependent on the similarity. See the full explanation below for the reasoning.
AI Risk Management and Controls
Question
An IS auditor reviewing documentation for an AI model notes that the modeler utilized a K-means clustering algorithm, which clusters data into categories for correlations and analysis. Which of the following is the MOST important risk for the auditor to consider?
Options
- AK-means clustering is not a common data clustering method due to its complexity and difficulty
- BK-means clustering requires the modeler to supervise the learning analysis, which can introduce
- CK-means clustering algorithms are significantly sensitive to outliers and dependent on the similarity
- DK-means clustering determines the number of clusters for the modeler without supervision.
Topics
#K-means Clustering#AI Risk Management#Outliers#IS Audit
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