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Snowflake Exam DSA-C02 Topic 1 Question 22 Discussion

Actual exam question for Snowflake's DSA-C02 exam
Question #: 22
Topic #: 1
[All DSA-C02 Questions]

Which method is used for detecting data outliers in Machine learning?

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Suggested Answer: C

By using ethnicity as a sensitive field, and comparing disparity between selection rates and performance metrics for each ethnicity value, you can evaluate the fairness of the model.


Contribute your Thoughts:

Fabiola
21 hours ago
Haha, I thought D) CMIYC stood for 'Catch Me If You Can' at first. Gotta keep those outliers on their toes, you know!
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Phillip
7 days ago
C) BOXI and D) CMIYC? Really? Those sound more like secret agent code names than ML techniques. Nice try, exam writer!
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Vicente
14 days ago
I was confused between A) Scaler and B) Z-Score, but Z-Score makes more sense for outlier detection.
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Alberta
16 days ago
B) Z-Score is the correct answer for detecting data outliers in Machine Learning. It's a standard technique to identify data points that deviate significantly from the mean.
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Larue
18 days ago
I'm not sure, but I think A) Scaler could also be used for detecting outliers.
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Lucina
20 days ago
I agree with Filiberto, Z-Score is commonly used for detecting outliers.
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Filiberto
21 days ago
I think the answer is B) Z-Score.
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