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NEW QUESTION: 1

You have a database that contains tables named Customer_CRMSystem and



Customer_CRMSystem

Customer_HRSystem





A. Option G
B. Option C
C. Option D
D. Option E
E. Option H
F. Option A
G. Option B
H. Option F
Answer: E
Explanation:
Explanation
To retain the nonmatching information by including nonmatching rows in the results of a join, use a full outer join. SQL Server provides the full outer join operator, FULL OUTER JOIN, which includes all rows from both tables, regardless of whether or not the other table has a matching value.

NEW QUESTION: 2

Refer to the exhibit. Which switch in this configuration becomes the root bridge?
A. SW1
B. SW4
C. SW2
D. SW3
Answer: D

NEW QUESTION: 3
トラフィックの着信をホストに通知するために使用されるイーサネットフレームのコンポーネントはどれですか。
A. データフィールド
B. プリマブル
C. タイプフィールド
D. フレーム区切りの開始
Answer: B

NEW QUESTION: 4
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 new experiment in Azure Learning learning Studio.
One class has a much smaller number of observations than the other classes in the training You need to select an appropriate data sampling strategy to compensate for the class imbalance.
Solution: You use the Synthetic Minority Oversampling Technique (SMOTE) sampling mode.
Does the solution meet the goal?
A. No
B. Yes
Answer: B
Explanation:
Explanation
SMOTE is used to increase the number of underepresented cases in a dataset used for machine learning.
SMOTE is a better way of increasing the number of rare cases than simply duplicating existing cases.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/smote