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NEW QUESTION: 1
There are two Workflow Systems, each associated with a different object store. The administrator would like to gather analytical information for both these Workflow Systems.
Which of the following tasks would accomplish the above?
A. Configure two different Case Analyzer Stores for each one of these Workflow Systems
B. Use Case Analyzer Process Task Manager to configure multiple Case Analyzer instances
C. Configure multiple Content Platform Engine instances
D. Only one Workflow System can be configured with Case Analytics capability within a single P8 Domain
Answer: B
Explanation:
Explanation/Reference:
Reference: https://www.ibm.com/support/knowledgecenter/en/SSGLW6_5.2.1/ com.ibm.p8.ce.admin.tasks.doc/bpfad020.htm
NEW QUESTION: 2
DRAG DROP
A customer starts a project to extend its server farm to Microsoft Azure. The customer plans to deploy virtual machines and storage for the virtual machines.
The project team includes the following members:
* A project owner who will manage the project spend
* An IT team that will deploy the virtual machines
The customer already has an Enterprise Agreement (EA) and will pay for the Azure services through the existing agreement.
Which portal should each project team member use? To answer, drag the appropriate portals to the correct team members. Each portal may be used once, 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:
NEW QUESTION: 3
Which command is used to query information about the available packages on a Debian system?
A. dpkg
B. apt-cache
C. apt-search
D. apt-get
E. dpkg-search
Answer: B
NEW QUESTION: 4
Why do you need to split a machine learning dataset into training data and test data?
A. To make sure your model is generalized for more than just the training data
B. So you can use one dataset for a wide model and one for a deep model
C. To allow you to create unit tests in your code
D. So you can try two different sets of features
Answer: A
Explanation:
The flaw with evaluating a predictive model on training data is that it does not inform you on how well the model has generalized to new unseen data. A model that is selected for its accuracy on the training dataset rather than its accuracy on an unseen test dataset is very likely to have lower accuracy on an unseen test dataset. The reason is that the model is not as generalized. It has specialized to the structure in the training dataset. This is called overfitting.
Reference: https://machinelearningmastery.com/a-simple-intuition-for-overfitting/