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NEW QUESTION: 1
새 구성원은 실행 단계에서 프로젝트에 참여합니다. 프로젝트 관리자는 새 구성원을 통합하기 위해 어떤 프로세스를 사용해야 합니까?
A. 팀 관리
B. 커뮤니케이션 관리
C. 자원 관리 계획
D. 커뮤니케이션 관리 계획
Answer: C
NEW QUESTION: 2
contoso.onmicrosoft.comという名前のAzure Active Directoryテナントに次のユーザーを含むAzureサブスクリプションがあります。
User1は、external.contoso.onmicrosoft.comという名前の新しいAzure Active Directoryテナントを作成します。
external.contoso.com.onmicrosoft.comで新しいユーザーアカウントを作成する必要があります。
解決策：User1にユーザーアカウントを作成するように指示します。
A. はい
B. いいえ
Answer: A
Explanation:
Explanation
Only a global administrator can add users to this tenant.
References:
https://docs.microsoft.com/en-us/azure/devops/organizations/accounts/add-users-to-azure-ad
NEW QUESTION: 3
A company selected Opera 10 as its corporate browser. Drive-by downloads are occurring and SONAR intercepts the resulting scripts. How should the company proceed to minimize the occurrence of drive-by downloads?
A. Upgrade to Opera 11.
B. Use Internet Explorer or Firefox.
C. Enable browser protection.
D. Reboot the Symantec Endpoint Protection client.
Answer: B
NEW QUESTION: 4
モデルの適合の問題を修正する必要があります。
順番に実行する必要がある3つのアクションはどれですか？回答するには、適切なアクションをアクションのリストから回答エリアに移動し、正しい順序に並べます。
Answer:
Explanation:
Explanation:
Step 1: Augment the data
Scenario: Columns in each dataset contain missing and null values. The datasets also contain many outliers.
Step 2: Add the Bayesian Linear Regression module.
Scenario: You produce a regression model to predict property prices by using the Linear Regression and Bayesian Linear Regression modules.
Step 3: Configure the regularization weight.
Regularization typically is used to avoid overfitting. For example, in L2 regularization weight, type the value to use as the weight for L2 regularization. We recommend that you use a non-zero value to avoid overfitting.
Scenario:
Model fit: The model shows signs of overfitting. You need to produce a more refined regression model that reduces the overfitting.
Incorrect Answers:
Multiclass Decision Jungle module:
Decision jungles are a recent extension to decision forests. A decision jungle consists of an ensemble of decision directed acyclic graphs (DAGs).
L-BFGS:
L-BFGS stands for "limited memory Broyden-Fletcher-Goldfarb-Shanno". It can be found in the wwo-Class Logistic Regression module, which is used to create a logistic regression model that can be used to predict two (and only two) outcomes.
References:
<https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/linear-regr ession>