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Exam DP-100 topic 5 question 15 discussion

Actual exam question from Microsoft's DP-100
Question #: 15
Topic #: 5
[All DP-100 Questions]

HOTSPOT -
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.
Hot Area:

Show Suggested Answer Hide Answer
Suggested Answer:
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.
Reference:
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

Comments

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ljljljlj
Highly Voted 4 years ago
On exam 2021/7/10
upvoted 8 times
azayra
4 years ago
You passed?
upvoted 6 times
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jefimija
Most Recent 8 months, 2 weeks ago
Linear Regression is not incorrect, maybe two options are correct.
upvoted 1 times
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AzureGeek79
9 months, 1 week ago
Would linear regression not be the right answer for first drop-down?
upvoted 1 times
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snegnik
2 years, 1 month ago
the table is not needed for the second question.
upvoted 1 times
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ning
3 years, 1 month ago
Yes, the given answer is correct: "Parameter Range: 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."
upvoted 4 times
ZoeJ
2 years, 2 months ago
https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/linear-regression?view=azureml-api-2#create-a-regression-model-using-online-gradient-descent
upvoted 1 times
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Tsardoz
3 years, 6 months ago
Not sure about parameter range. The only way this would work is if you had prior knwledge of the coefficients eg. by looking at the Bayesian results. Otherwise increasing number of epochs would be the most sensible approach.
upvoted 2 times
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