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NEW QUESTION: 1
Refer to the exhibit.

The exhibit shows output from a Mobility Master (MM) dashboard. What is a valid reason for the administrator to click the akamai square under applications?
A. to download a report about the usage of this application over time
B. to see the break down for only the roles, destinations, WLANs, and devices that use this application
C. to create filter rules in order to control wireless user access to this application
D. to set up bandwidth rule in order to control wireless user access to this application
Answer: B

NEW QUESTION: 2
You are the Microsoft 365 administrator for a company.
You need to find all general availability features for SharePoint Online.
Which two options should you select on the Microsoft 365 Roadmap page? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation

References:
https://www.microsoft.com/en-us/microsoft-365/roadmap?filters=Launched%2CWindows%2COnline%2CO365

NEW QUESTION: 3
You need to select a feature extraction method.
Which method should you use?
A. Mutual information
B. Permutation Feature Importance
C. Kendall correlation
D. Mood's median test
Answer: C
Explanation:
Explanation
In statistics, the Kendall rank correlation coefficient, commonly referred to as Kendall's tau coefficient (after the Greek letter ), is a statistic used to measure the ordinal association between two measured quantities.
It is a supported method of the Azure Machine Learning Feature selection.
Scenario: When you train a Linear Regression module using a property dataset that shows data for property prices for a large city, you need to determine the best features to use in a model. You can choose standard metrics provided to measure performance before and after the feature importance process completes. You must ensure that the distribution of the features across multiple training models is consistent.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/feature-selection-modules