Azure Machine Learning activity

Display Name

Function:

Specifies the activity name that shows in your process.

Accepted Values:

One line of text that can have spaces.

Default Value:

None

Accepts Process Data Variables:

No

Example:

This is a common configuration field that is used in many examples. Refer to:

• Examples - Step-by-step use case examples, information about what types of examples are provided in the AgilePoint NX Product Documentation, and other resources where you can find more examples.

Description

Function:

Specifies an optional text description for your activity.

Accepted Values:

More than one line of text.

Default Value:

None

Accepts Process Data Variables:

No

Add Score Model

Function:

Creates a score model with a name you specify.

Edit

Function:

Changes the selected item.

Delete

Function:

Deletes the selected item.

Example:

Refer to:

• The videos on this page

Azure Machine Learning

Function:

Specifies the access token that connects to your Microsoft Azure Machine Learning service.

Accepted Values:

A list of access tokens configured for your environment.

Default Value:

None

Accepts Process Data Variables:

No

Example:

Refer to:

• (Example) How to Get the Access Token Credentials from Microsoft Azure Machine Learning

Add Token

Opens this Screen:

Access Token for Microsoft Azure Machine Learning

Function of this Screen:

Configure an access token to connect to Microsoft Azure Machine Learning.

Example:

Refer to:

• (Example) How to Get the Access Token Credentials from Microsoft Azure Machine Learning

Activity

Function:

Specifies an activity in your process you want Microsoft Microsoft Azure Machine Learning to use in your score model.

Accepted Values:

An activity from the list.

Default Value:

None

Accepts Process Data Variables:

No

On Event

Function:

Specifies the activity's event you want to use in your score model.

1. For a human task activity, you can select events for the activity or the tasks the activity creates.
2. For a system activity, you can select only events for the activity.

Accepted Values:

• Assign Work Item - Azure Machine Learning runs when a task is Assigned to a participant.
• Complete Work Item - Azure Machine Learning runs when a task is Completed.
• Cancel Work Item - Azure Machine Learning runs when a task is Cancelled.
• Enter Activity Instance - Azure Machine Learning runs when the activity starts.
• Leave Activity Instance - Azure Machine Learning runs when the the activity ends.
• Reassign Work Item - Azure Machine Learning runs when a task is Reassigned.
• Work Item Assigned - Azure Machine Learning runs when a task is Assigned to a participant.
• Work Item Overdue - Azure Machine Learning runs when a task is Overdue.

Default Value:

None

Request Mapping

Function:

Connects the Microsoft Azure Machine Learning API request parameter to your schema. This is mandatory only if the request passes data from the process schema to parameters in the Azure Machine Learning API.

To Open this Field:

1. On the Machine Learning Configuration screen, click the Request tab.

Accepted Values:

Click the Schema Mapping button to open the Schema Mapper.

Use this screen to connect the request to the data model for your process.

Default Value:

None

Limitations:

Some information about third-party integrations is outside the scope of the AgilePoint NX Product Documentation, and it is the responsibility of the vendors who create and maintain these technologies to provide this information. This includes specific business uses cases and examples; explanations for third-party concepts; details about the data models and input and output data formats for third-party technologies; and various types of IDs, URL patterns, connection string formats, and other technical information that is specific to the third-party technologies. For more information, refer to Where Can I Find Information and Examples for Third-Party Integrations?

Map Response to AgilePoint Schema

Function:

Specifies the connection from the Microsoft Azure Machine Learning API response parameter to your schema.

To Open this Field:

1. On the Machine Learning Configuration screen, click the Response tab.

Accepted Values:

Click the Schema Mapping button to open the Schema Mapper.

Use this screen to connect the response to the data model for your process.

Default Value:

None

Limitations:

Some information about third-party integrations is outside the scope of the AgilePoint NX Product Documentation, and it is the responsibility of the vendors who create and maintain these technologies to provide this information. This includes specific business uses cases and examples; explanations for third-party concepts; details about the data models and input and output data formats for third-party technologies; and various types of IDs, URL patterns, connection string formats, and other technical information that is specific to the third-party technologies. For more information, refer to Where Can I Find Information and Examples for Third-Party Integrations?

Store the Response in Custom Attribute

Function:

Specifies the process data variable that stores the responses from the Microsoft Azure Machine Learning API method call.

To Open this Field:

1. On the Machine Learning Configuration screen, click the Response tab.

Accepted Values:

A process data variable that accepts an alphanumeric string in JSON format.

Default Value:

None

Accepts Process Data Variables:

Yes

Example:

[{"Results":{"output1":{"type":"table","value":{"ColumnNames":["Age","State","CardType","Scored Labels","Scored Probabilities"],"ColumnTypes":["Int32","String","String","String","Double"],"Values":[["21","CA","visa","High","0.0183113589882851"]]}}}}]