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GCP Professional Data Engineer Practice Question

Your team has trained a binary logistic-regression model called marketing.churn_model in BigQuery ML using the default automatic data split (80% training, 20% evaluation). You now want to inspect the model's quality without incurring additional query costs or creating a separate test table. Which SQL statement both satisfies these requirements and returns metrics such as accuracy, precision, recall, F1 score, and log_loss?

  • SELECT * FROM ML.FEATURE_INFO(MODEL marketing.churn_model);

  • SELECT * FROM ML.EVALUATE(MODEL marketing.churn_model, TABLE marketing.test_churn);

  • SELECT * FROM ML.PREDICT(MODEL marketing.churn_model, (SELECT * FROM marketing.customers));

  • SELECT * FROM ML.EVALUATE(MODEL marketing.churn_model);

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