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Snowflake Exam DSA-C02 Topic 1 Question 19 Discussion

Actual exam question for Snowflake's DSA-C02 exam
Question #: 19
Topic #: 1
[All DSA-C02 Questions]

You are training a binary classification model to support admission approval decisions for a college degree program.

How can you evaluate if the model is fair, and doesn't discriminate based on ethnicity?

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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.


by Leontine at May 18, 2024, 08:15 AM

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Dwight
9 months ago
Haha, D? Really? That's like saying 'None of the above' to a multiple-choice question on fairness. Good one!
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Serina
8 months ago
Haha, D? Really? That's like saying 'None of the above' to a multiple-choice question on fairness. Good one!
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Shenika
9 months ago
C) Compare disparity between selection rates and performance metrics across ethnicities.
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Gregg
9 months ago
A) Evaluate each trained model with a validation dataset and use the model with the highest accuracy score.
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Osvaldo
9 months ago
B is tempting, but removing the ethnicity feature doesn't solve the problem. You need to actually analyze the model's behavior across different groups.
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Sharee
9 months ago
B) Remove the ethnicity feature from the training dataset.
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Boris
9 months ago
C) Compare disparity between selection rates and performance metrics across ethnicities.
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Josue
9 months ago
A) Evaluate each trained model with a validation dataset and use the model with the highest accuracy score.
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Chan
10 months ago
Definitely not A. Accuracy alone doesn't guarantee fairness. Gotta look at the details, you know?
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Janey
9 months ago
C) Compare disparity between selection rates and performance metrics across ethnicities.
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Noelia
9 months ago
B) Remove the ethnicity feature from the training dataset.
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Corinne
9 months ago
C) Compare disparity between selection rates and performance metrics across ethnicities.
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Glory
9 months ago
B) Remove the ethnicity feature from the training dataset.
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Tiera
10 months ago
Option C is the way to go. Checking for disparities in selection rates and performance metrics across ethnicities is crucial for evaluating fairness.
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Eliz
9 months ago
A) Evaluate each trained model with a validation dataset and use the model with the highest accuracy score.
upvoted 0 times
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Avery
10 months ago
C) Compare disparity between selection rates and performance metrics across ethnicities.
upvoted 0 times
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