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NEW QUESTION: 1
Identify the option that accurately describes how to set a report filter from code by using Connect Web Services for SOAP.
A. An array of AnalyticsReportFiiter can be dynamically created and set on the AnalyticsReport object that is passed to the RightNowSyncPortciient. RunAnalyticsReport method.
B. RightNowSyncPortciient.GetReportFiiters must be used first to retrieve the report filters from the report.
RightNowSyncPortciient .SetReportFiiters can then be used to set the filters in code. The report can then be run USing RightNowSyncPortciient. RunAnalyticsReport-
C. Report filters cannot be set from code. The user is required to set the filter in the Analytics Report Designer of the Agent Desktop.
D. RightNowSyncPortciient.setReportFiiters can be used directly to set the filters in code. The report can then be run using RightNowSyncPortciient. RunAnalyticsReport.
Answer: B

NEW QUESTION: 2
Historical reports can be scheduled to email to a user, but they can also be scheduled to do what?
A. Export to a folder
B. Print
C. Display in the User interface
D. Refresh every 15 minutes
Answer: B
Explanation:
Explanation/Reference:
Explanation:
All historical reports created within CCC can be scheduled for individual delivery to anyone via email.
Reports can also be scheduled to multiple network printers.
Reference https://downloads.avaya.com/elmodocs2/ip_office/DOCS3_0/DATA/Additional/mergedProjects/ productdescription/ccc_v5/compactcontactcenter.htm

NEW QUESTION: 3
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:
Box 1: Yes
In machine learning, if you have labeled data, that means your data is marked up, or annotated, to show the target, which is the answer you want your machine learning model to predict.
In general, data labeling can refer to tasks that include data tagging, annotation, classification, moderation, transcription, or processing.
Box 2: No
Box 3: No
Accuracy is simply the proportion of correctly classified instances. It is usually the first metric you look at when evaluating a classifier. However, when the test data is unbalanced (where most of the instances belong to one of the classes), or you are more interested in the performance on either one of the classes, accuracy doesn't really capture the effectiveness of a classifier.
Reference:
https://www.cloudfactory.com/data-labeling-guide
https://docs.microsoft.com/en-us/azure/machine-learning/studio/evaluate-model-performance