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NEW QUESTION: 1
注：この質問は、同じシナリオを提示する一連の質問の一部です。シリーズの各質問には、記載された目標を達成する可能性のある独自のソリューションが含まれています。一部の質問セットには複数の正しい解決策がある場合もあれば、正しい解決策がない場合もあります。
このセクションの質問に回答すると、その質問に戻ることはできません。その結果、これらの質問はレビュー画面に表示されません。
contoso.comという名前のMicrosoft Azure Active Directory（Azure AD）テナントがあります。
Workspace1という名前のAzure Advanced Threat Protection（ATP）ワークスペースを作成します。
テナントには、次の表に示すユーザーが含まれます。

Azure ATPセンサーの構成を変更する必要があります。
解決策：Azure ATPセンサー構成を変更するようにUser1に指示します。
これは目標を達成していますか？
A. はい
B. いいえ
Answer: A
Explanation:
Explanation
Only Azure ATP administrators can modify the sensors.
References:
https://docs.microsoft.com/en-us/azure-advanced-threat-protection/atp-role-groups

NEW QUESTION: 2
When an administrator creates a new access policy in the Visual Policy Editor, which three options are included by default? (Choose three.)
A. A fallback option
B. An Allow Ad box
C. A Deny End box
D. An empty Resource Assign item
E. A Block All option
F. A Start box
Answer: A,C,F

NEW QUESTION: 3
You are using a decision tree algorithm. You have trained a model that generalizes well at a tree depth equal to
10.
You need to select the bias and variance properties of the model with varying tree depth values.
Which properties should you select for each tree depth? To answer, select the appropriate options in the answer area.

Answer:
Explanation:

Explanation

In decision trees, the depth of the tree determines the variance. A complicated decision tree (e.g. deep) has low bias and high variance.
Note: In statistics and machine learning, the bias-variance tradeoff is the property of a set of predictive models whereby models with a lower bias in parameter estimation have a higher variance of the parameter estimates across samples, and vice versa. Increasing the bias will decrease the variance. Increasing the variance will decrease the bias.
References:
https://machinelearningmastery.com/gentle-introduction-to-the-bias-variance-trade-off-in-machine-learning/