Duplicate and inactive requests negatively impact the quality of
predictions.
If you want to clean up the data before it’s fed to the
Machine Learning API, create exclusion rules for data ingestion. These rules help to
filter out the duplicate or inactive data, so they’re excluded from being ingested by
the ML model.
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In the Setup and Maintenance work area, go to the following:
- Offering: Help Desk
- Functional Area: Email Communication Channels
- Task: Manage Email Configuration, Registration, and Validation
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In the Inbound Email Configuration and Validation page, navigate to the SR
Classification area.
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In the Ingestion Exclusion Rule area, click Add.
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In the Object field, select one of the following:
Service Request, Internal Service Request, or HR Help Desk Request.
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In the Attribute field, select the object attribute
based on which you want to filter the data.
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In the Operator field, select a suitable operator such
as Contains, Equals, or
Is Not Null, depending on the rule you’re
creating.
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In the Value field, specify the value for the exclusion
rule.
Here are some examples:
- Requests created by messages from WhatsApp: Here, you could select the
attribute as Channel Type, operator as
Equals or Contains,
and the value as WhatsApp.
- Requests created by a user whose email pattern contains test: These
requests aren’t to be considered for training the ML model, because this
would be test data.
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Click Save.