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NEW QUESTION: 1
機械学習モデルを作成しています。
データ内の外れ値を識別する必要があります。
どの2つの視覚エフェクトを使用できますか？それぞれの正解は完全な解決策を提示します。
注：それぞれの正しい選択には1ポイントの価値があります。
注：それぞれの正しい選択には1ポイントの価値があります。
A. Venn diagram
B. box plot
C. random forest diagram
D. scatter
E. ROC curve
Answer: B,D
Explanation:
The box-plot algorithm can be used to display outliers.
One other way to quickly identify Outliers visually is to create scatter plots.
References:
https://blogs.msdn.microsoft.com/azuredev/2017/05/27/data-cleansing-tools-in-azure-machine-learning/

NEW QUESTION: 2
대규모 정부 기관의 프로젝트 관리자가 각 개별 컴퓨터의 운영 체제 업그레이드를 구현하고 있습니다. 부서 관리자는 변경 사항에 대한 정보를 받지 못했으며 계획대로 변경이 이루어지지 않을 것이라고 불평합니다.
향후 이러한 상황을 피하기 위해 프로젝트 관리자는 무엇을 할 수 있습니까?
A. 비즈니스 문서를 미리 검토하고 적절히 변경하십시오.
B. 관리자가 검토 할 여러 옵션 식별
C. 주요 이해 관계자 식별 및 프로세스 초기에 참여
D. 가능한 위험 분석 및 실행 가능한 비상 계획 작성
Answer: C

NEW QUESTION: 3
Which components can use Active Directory authorization attributes for the decision-making process? (Select two.)
A. Enforcement policy
B. Profiling policy
C. Role Mapping policy
D. Posture policy
E. Certificate validation policy
Answer: A,C
Explanation:
Explanation
C: Role Mappings Page - Rules Editor Page Parameters

D: Enforcement Policy Attributes tab Parameters

References:
http://www.arubanetworks.com/techdocs/ClearPass/Aruba_CPPMOnlineHelp/Content/CPPM_UserGuide/identi
http://www.arubanetworks.com/techdocs/ClearPass/Aruba_CPPMOnlineHelp/Content/CPPM_UserGuide/Policy