DSA-C03 Exam Dumps | You are developing a churn prediction model and want to track its performance across different model

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Question 51

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Question 51/143

You are developing a churn prediction model and want to track its performance across different model versions using the Snowflake Model Registry. After registering a new model version, you need to log evaluation metrics (e.g., AUC, F 1-score) and custom tags associated with the training run. Assuming you have a registered model named 'churn_model' with version 'v2', which of the following code snippets demonstrates the correct way to log these metrics and tags using the Snowflake Python Connector and the 'ModelRegistry' API?

Correct Answer: A

Option A is correct. It first retrieves the specific model version using , and then calls and 'set_tag' on the returned 'version' object. The other options either attempt to call these methods directly on the "ModelRegistry' object (incorrect as these are version-specific operations) or use incorrect syntax for accessing versions.

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