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NEW QUESTION: 1
Which three authentication services can administrator use to authenticate admins into the Palo Alto Networks NGFW without defining a corresponding admin account on the local firewall? (Choose three.)
A. Kerberos
B. PAP
C. LDAP
D. RADIUS
E. SAML
F. TACACS+
Answer: A,C,E

NEW QUESTION: 2
Your network contains an Active Directory forest.
You need to add a new user principal name (UPN) suffix to the forest.
Which tool should you use?
A. Active Directory Users and Computers
B. Active Directory Sites and Services
C. Active Directory Administrative Center
D. Active Directory Domains and Trusts
Answer: D
Explanation:
Reference: http://www.kassapoglou.com/windows-server-2008-lesson-23-video-creating-a-user/
Demonstration adding a UPN Suffix
To add or modify a UPN suffix for your forest, open Active Directory Domains and Trusts from the start menu. Right click Active Directory Domains and Trusts at the top and open the properties. From here you can add and remove additional domain UPN suffixes for the forest.

NEW QUESTION: 3
匿名の訪問者がランディングページのフォームに正常に記入した合計回数はどこで確認できますか。
A. ランディングページは、独自のフォーム送信の下でレポートします
B. ランディングページ変換中のレポート
C. 提出書類全体のフォームレポート
D. 合計ユニークフォーム提出の下のフォームレポート
Answer: B

NEW QUESTION: 4
You need to replace the missing data in the AccessibilityToHighway columns.
How should you configure the Clean Missing Data module? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation

Box 1: Replace using MICE
Replace using MICE: For each missing value, this option assigns a new value, which is calculated by using a method described in the statistical literature as "Multivariate Imputation using Chained Equations" or
"Multiple Imputation by Chained Equations". With a multiple imputation method, each variable with missing data is modeled conditionally using the other variables in the data before filling in the missing values.
Scenario: The AccessibilityToHighway column in both datasets contains missing values. The missing data must be replaced with new data so that it is modeled conditionally using the other variables in the data before filling in the missing values.
Box 2: Propagate
Cols with all missing values indicate if columns of all missing values should be preserved in the output.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/clean-missing-data

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