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NEW QUESTION: 1
What is required before ordering file snapshots from a VNX array in ViPR?
A. Maximum native continuous copies greater than 0
B. Snapshot license on the ViPR Controller
C. SnapMover license in the VNX
D. SnapSure license in the VNX
Answer: D

NEW QUESTION: 2
Which of the following biometric parameters are better suited for authentication use over a long period of time?
A. Retina pattern
B. Signature dynamics
C. Iris pattern
D. Voice pattern
Answer: C

NEW QUESTION: 3
What verification must be conducted before assigning Job or Abstract Roles?
A. For each job or abstract role, review the department that it carries so you understand which users should be provisioned with the department, or which adjustments your enterprise requires before the department can be provisioned.
B. For each job or abstractrole, review the grade that it carries so you understand which users should be provisioned with the department, or which adjustments your enterprise requires before the grade can be provisioned.
C. For each job or abstract role, review the Job data that it carries so you understand which users should be provisioned with the job, or which adjustments your enterprise requires before the job can be provisioned.
D. For each job or abstract role, review the policies and permission grants that it carries so you understand which users should be provisioned with what policies, or which adjustments your enterprise requires before the policies can be provisioned.
E. For each job or abstract role, review the duties, role hierarchy, and policies that it carries so you understand which users should be provisioned with the role, or which adjustments your enterprise requires before the role can be provisioned.
Answer: D

NEW QUESTION: 4
You have a model with a large difference between the training and validation error values.
You must create a new model and perform cross-validation.
You need to identify a parameter set for the new model using Azure Machine Learning Studio.
Which module you should use for each step? To answer, drag the appropriate modules to the correct steps.
Each module may be used once or more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation

Box 1: Split data
Box 2: Partition and Sample
Box 3: Two-Class Boosted Decision Tree
Box 4: Tune Model Hyperparameters
Integrated train and tune: You configure a set of parameters to use, and then let the module iterate over multiple combinations, measuring accuracy until it finds a "best" model. With most learner modules, you can choose which parameters should be changed during the training process, and which should remain fixed.
We recommend that you use Cross-Validate Model to establish the goodness of the model given the specified parameters. Use Tune Model Hyperparameters to identify the optimal parameters.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/partition-and-sample