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NEW QUESTION: 1
You are developing a linear regression model in Azure Machine Learning Studio. You run an experiment to compare different algorithms.
The following image displays the results dataset output:
Use the drop-down menus to select the answer choice that answers each question based on the information presented in the image.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: Boosted Decision Tree Regression
Mean absolute error (MAE) measures how close the predictions are to the actual outcomes; thus, a lower score is better.
Box 2:
Online Gradient Descent: If you want the algorithm to find the best parameters for you, set Create trainer mode option to Parameter Range. You can then specify multiple values for the algorithm to try.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/evaluate-model
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/linear-regression
NEW QUESTION: 2
How many impressions does an advert need to have to show a relevance score?
A. 0
B. 1
C. 2
D. 3
Answer: C
Explanation:
Explanation: The relevance score for an ad is shown once it has had more than 500 impressions.
NEW QUESTION: 3
An administrator is building a parent virtual machine for a View desktop pool and needs to enable users to log onto the virtual desktops.
To which group should the administrator assign the users?
A. Local Terminal Server Users group
B. Global Terminal Server Users group
C. Global Remote Desktop Users group
D. Local Remote Desktop Users group
Answer: D