DSA-C03 Exam Dumps | You are evaluating a binary classification model's performance using the Area Under the ROC Curve (AUC).

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Snowflake.DSA-C03.v2026-01-08.q143
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Question 12/143

You are evaluating a binary classification model's performance using the Area Under the ROC Curve (AUC). You have the following predictions and actual values. What steps can you take to reliably calculate this in Snowflake, and which snippet represents a crucial part of that calculation? (Assume tables 'predictions' with columns 'predicted_probability' (FLOAT) and 'actual_value' (BOOLEAN); TRUE indicates positive class, FALSE indicates negative class). Which of the below code snippet should be used to calculate the 'True positive Rate' and 'False positive Rate' for different thresholds

A. Calculate AUC directly within a Snowpark Python UDF using scikit-learn's function. This avoids data transfer overhead, making it highly efficient for large datasets. No further SQL is needed beyond querying the predictions data.

B. The AUC cannot be reliably calculated within Snowflake due to limitations in SQL functionality for statistical analysis.

C. Using only SQL, Create a temporary table with calculated True Positive Rate (TPR) and False Positive Rate (FPR) at different probability thresholds. Then, approximate the AUC using the trapezoidal rule.

D. Export the 'predicted_probability' and 'actual_value' columns to a local Python environment and calculate the AUC using scikit-learn.

E. The best way to calculate AUC is to randomly guess the probabilities and see how it performs.

Correct Answer: A,C

Options A and C are correct. Option A demonstrates calculating AUC directly within Snowflake using a Snowpark Python UDF and scikit-learn's . This is efficient for large datasets as it avoids data transfer. Option C correctly outlines the process of calculating TPR and FPR using SQL and approximating AUC using the trapezoidal rule, another viable approach within Snowflake. Option B is incorrect; AUC can be calculated reliably within Snowflake. Option D is inefficient due to data transfer. Option E is blatantly incorrect.

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