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NEW QUESTION: 1
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
B. No
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.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/evaluate-model

NEW QUESTION: 2
Dell EMC Unity XTスナップショットで使用されているどのテクノロジーが正確に説明されていますか？
A. 最初の書き込み時のコピーでは、スナップショットを作成するためにストレージリソースは必要ありません。書き込みは親プールにコピーされます。
B. 書き込み時のリダイレクトにはスナップショットを作成するためのストレージリソースは必要ありません。書き込みは親プールにリダイレクトされます
C. 最初の書き込み時のコピーには、ポイントインタイムビューを維持するために変更された元のデータを保持するために予約されたストレージリソースが必要です
D. リダイレクト時の書き込みには、ポイントインタイムビューを保持するために変更された元のデータを保持するために予約されたストレージリソースが必要です
Answer: D

NEW QUESTION: 3
To return from a Data Abort handler and re-execute the aborting instruction, what value should be loaded to the PC?
A. PC=LR44
B. PC=LR
C. PC=LR-4
D. PC=LR-8
Answer: D