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NEW QUESTION: 1
A security administrator is tackling issues related to authenticating users at a remote site. There have been a large number of security incidents that resulted from either tailgating or impersonation of authorized users with valid credentials. The security administrator has been told to implement multifactor authentication in order to control facility access. To secure access to the remote facility, which of the following could be implemented without increasing the amount of space required at the entrance?
A. MOTD challenge and PIN pad
B. Retina scanner and fingerprint reader
C. Voice recognition and one-time PIN token
D. One-time PIN token and proximity reader
Answer: C
Explanation:
Authentication systems or methods are based on one or more of these five factors:
Something you know, such as a password or PIN
Something you have, such as a smart card, token, or identification device
Something you are, such as your fingerprints or retinal pattern (often called biometrics)
Something you do, such as an action you must take to complete authentication
Somewhere you are (this is based on geolocation)
Multifactor authentication is authentication that uses two of more of the authentication factors
listed above.
In this question, we can use voice recognition (something you are) and a one-time PIN token
(something you have) to provide two factors of authentication. The one-time PIN token is a small
device that generates a one-time PIN to enable access.

NEW QUESTION: 2
マーケティング担当者は、データ拡張機能に保存されたデータからセグメントを作成するためのシンプルなツールが必要です。どのようにアドバイスしますか？
A. アクティビティのクエリ
B. 対策
C. グループ
D. データフィルター
Answer: D

NEW QUESTION: 3
You need to identify the methods for dividing the data according to the testing requirements.
Which properties should you select? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation:
Scenario: Testing
You must produce multiple partitions of a dataset based on sampling using the Partition and Sample module in Azure Machine Learning Studio.
Box 1: Assign to folds
Use Assign to folds option when you want to divide the dataset into subsets of the data. This option is also useful when you want to create a custom number of folds for cross-validation, or to split rows into several groups.
Not Head: Use Head mode to get only the first n rows. This option is useful if you want to test a pipeline on a small number of rows, and don't need the data to be balanced or sampled in any way.
Not Sampling: The Sampling option supports simple random sampling or stratified random sampling. This is useful if you want to create a smaller representative sample dataset for testing.
Box 2: Partition evenly
Specify the partitioner method: Indicate how you want data to be apportioned to each partition, using these options:
* Partition evenly: Use this option to place an equal number of rows in each partition. To specify the number of output partitions, type a whole number in the Specify number of folds to split evenly into text box.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/algorithm-module-reference/partition-and-sample