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NEW QUESTION: 1
You have a Microsoft Azure Active Directory (Azure AD) tenant named contoso.com that contain the users shown in the following table.

You have a computer named Computer1 that runs Windows 10.

User1 joins Computer1 to Azure AD by using [email protected].
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation

NEW QUESTION: 2
Because of learner conversation and questioning, a course has moved away from the intended learning objectives. Which of the following techniques can bring the learners back on track?
A. Guide the discussion back to the objective.
B. Finish the conversation and adjust the remaining class time and objectives.
C. Overlook the off-topic conversation and continue with the discussion.
D. Give the class an extra break to refocus the group.
Answer: A
Explanation:
Explanation/Reference:
Explanation:

NEW QUESTION: 3
A Data Scientist is developing a machine learning model to classify whether a financial transaction is fraudulent. The labeled data available for training consists of 100,000 non- fraudulent observations and 1,000 fraudulent observations.
The Data Scientist applies the XGBoost algorithm to the data, resulting in the following confusion matrix when the trained model is applied to a previously unseen validation dataset. The accuracy of the model is 99.1%, but the Data Scientist has been asked to reduce the number of false negatives.

Which combination of steps should the Data Scientist take to reduce the number of false positive predictions by the model? (Choose two.)
A. Increase the XGBoost scale_pos_weight parameter to adjust the balance of positive and negative weights.
B. Decrease the XGBoost max_depth parameter because the model is currently overfitting the data.
C. Change the XGBoost eval_metric parameter to optimize based on AUC instead of error.
D. Change the XGBoost eval_metric parameter to optimize based on rmse instead of error.
E. Increase the XGBoost max_depth parameter because the model is currently underfitting the data.
Answer: A,C

NEW QUESTION: 4


Answer:
Explanation:

Explanation
to allow local management of the cluster to be configured.