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NEW QUESTION: 1
You plan to install Oracle Grid Infrastructure for a Standalone Server and Oracle Database for the first time on a server.
Examine this command and its outcome:
Which two are true? (Choose two.)
A. oracle must be the owner of every Oracle Database installation.
B. oracle will be an owner of the Oracle Inventory.
C. oracle can own an Oracle Database installation but not an Oracle Grid Infrastructure installation.
D. The user account, oracle, and group, oinstall, can be used for all Oracle software installations.
E. oracle will be granted the SYSASM privilege when installing the Oracle Database software.
Answer: B,D
NEW QUESTION: 2
A physical Windows 2008 R2 Server is converted to a virtual machine using VMware vCenter Converter. Upon completion of the conversion and subsequent power on operation, the virtual machine fails to boot and the message below is observed in the
Console of the virtual machine:
STOP 0x0000007B INACCESSIBLE_BOOT_DEVICE
Which two potential issues may be causing this boot failure? (Choose two.)
A. A snapshot was taken immediately after the conversion completed.
B. An incorrect SCSI controller was selected during conversion.
C. Incompatible software drivers were migrated into the virtual machine from the source machine.
D. The vmdk file backing the virtual machine was thick provisioned.
Answer: B,C
NEW QUESTION: 3
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