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Question 44 - DP-100 discussion

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Note: This question-is part of a series of questions that present the same scenario. Each question-in the series contains a unique solution that might meet the stated goals. Some question-sets might have more than one correct solution, while others might not have a correct solution.

After you answer a question-in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.

You are creating a model to predict the price of a student's artwork depending on the following variables: the student's length of education, degree type, and art form.

You start by creating a linear regression model.

You need to evaluate the linear regression model.

Solution: Use the following metrics: Mean Absolute Error, Root Mean Absolute Error, Relative Absolute Error, Accuracy, Precision, Recall, F1 score, and AUC.

Does the solution meet the goal?

A.
Yes
Answers
A.
Yes
B.
No
Answers
B.
No
Suggested answer: B

Explanation:

Accuracy, Precision, Recall, F1 score, and AUC are metrics for evaluating classification models.

Note: Mean Absolute Error, Root Mean Absolute Error, Relative Absolute Error are OK for the linear regression model.

Reference:

https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/evaluate-model

asked 02/10/2024
Giorgio Bertocchi
39 questions
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