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Does the solution meet the goal?

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You are using Azure Machine Learning to run an experiment that trains a classification model.

You want to use Hyperdrive to find parameters that optimize the AUC metric for the model.

You configure a HyperDriveConfig for the experiment by running the following code:

You plan to use this configuration to run a script that trains a random forest model and then tests it with validation data. The label values for the validation data are stored in a variable named y_test variable, and the predicted probabilities from the model are stored in a variable named y_predicted.

You need to add logging to the script to allow Hyperdrive to optimize hyperparameters for the AUC metric.

Solution: Run the following code:

Does the solution meet the goal?
A . Yes
B. No

Answer: B

Explanation:

Use a solution with logging.info(message) instead.

Note: Python printing/logging example:

logging.info(message)

Destination: Driver logs, Azure Machine Learning designer

Reference: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-debug-pipelines

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