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NEW QUESTION: 1
会社にはメインオフィスとMicrosoft 365サブスクリプションがあります。
物理的にオフィスにいないすべてのユーザーに条件付きアクセスを使用して、Microsoft Azure Multi-Factor Authentication（MFA）を実施する必要があります。
構成には何を含める必要がありますか？
A. サインインリスクポリシー
B. Azure MFAサーバー
C. Azure Active Directory（Azure AD）の名前付き場所
D. ユーザーリスクポリシー
Answer: C
Explanation:
説明
参照：
https://docs.microsoft.com/en-us/azure/active-directory/conditional-access/location-condition

NEW QUESTION: 2
開発者は、DescribeSObjectResultから、現在のユーザがApexでオブジェクトのレコードを作成できるかどうかをどのように判断できますか？
A. isInsertable（）メソッドを使用する。
B. canCreate（）メソッドを使用。
C. hasAccess（）メソッドを使用する。
D. isCreatable（）メソッドを使用する。
Answer: D

NEW QUESTION: 3
You are performing a classification task in Azure Machine Learning Studio.
You must prepare balanced testing and training samples based on a provided data set.
You need to split the data with a 0.75:0.25 ratio.
Which value should you use for each parameter? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation:
Box 1: Split rows
Use the Split Rows option if you just want to divide the data into two parts. You can specify the percentage of data to put in each split, but by default, the data is divided 50-50.
You can also randomize the selection of rows in each group, and use stratified sampling. In stratified sampling, you must select a single column of data for which you want values to be apportioned equally among the two result datasets.
Box 2: 0.75
If you specify a number as a percentage, or if you use a string that contains the "%" character, the value is interpreted as a percentage. All percentage values must be within the range (0, 100), not including the values 0 and 100.
Box 3: Yes
To ensure splits are balanced.
Box 4: No
If you use the option for a stratified split, the output datasets can be further divided by subgroups, by selecting a strata column.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/split-data