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NEW QUESTION: 1
What is the Avaya supported method of backing up an Avaya Aura Session Manager (SM) data base?
A. Wait for the overnight Backup process to send you a copy of the .tar file automatically.
B. Connect a Memory Drive into the SM Server with an automatic Backup-making script.
C. Access the SM Command Line Interface (CLI) and perform a Backup manually.
D. Perform the backup from an Avaya Aura System Manager.
Answer: D
NEW QUESTION: 2
You can use a follow-up function to trigger a Workflow task.
A. Correct
B. Incorrect
Answer: B
NEW QUESTION: 3
You have a Microsoft 365 subscription.
You plan to enable Microsoft Azure Information Protection.
You need to ensure that only the members of a group named PilotUsers can protect content.
What should you do?
A. Create an Azure Information Protection policy.
B. Run the Add-AadrmRoleBasedAdministrator cmdlet.
C. Configure the protection activation status for Azure Information Protection.
D. Run the Set-AadrmOnboardingControlPolicy cmdlet.
Answer: D
Explanation:
Explanation/Reference:
Explanation:
If you don't want all users to be able to protect documents and emails immediately by using Azure Rights Management, you can configure user onboarding controls by using the Set-AadrmOnboardingControlPolicy References:
https://docs.microsoft.com/en-us/azure/information-protection/activate-service
NEW QUESTION: 4
You create a binary classification model.
You need to evaluate the model performance.
Which two metrics can you use? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
A. mean absolute error
B. coefficient of determination
C. accuracy
D. precision
E. relative absolute error
Answer: C,D
Explanation:
The evaluation metrics available for binary classification models are: Accuracy, Precision, Recall, F1 Score, and AUC.
Note: A very natural question is: 'Out of the individuals whom the model, how many were classified correctly (TP)?' This question can be answered by looking at the Precision of the model, which is the proportion of positives that are classified correctly.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio/evaluate-model-performance
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