Amazon Machine Learning activity

An activity that gives predictions based on an Amazon Machine Learning model for the AgilePoint NX app. You can also skip steps in a process if the conditions specified in the Amazon Machine Learning model occur.

Amazon Machine Learning analyzes the data to create a predication. For example, you have college enrollment data based on historical data. The college enrollment data contains grade, family income, course, and previous school. Based on the college enrollment data, Amazon Machine Learning can predict whether the candidate qualifies for admission to your school.


Amazon Machine Learning activity

Configure the Amazon Machine Learning activity

To configure the Amazon Machine Learning activity, do the procedure in this topic.

Prerequisites

Good to Know

You can not connect this activity to your process flow. To configure this activity, put it on the process model not connected to any other activities to configure it.

How to Start

  1. Open Process Builder.

    For information about how to open this screen, refer to Process Builder.


    Open Process Builder
  2. In the Process Builder, in the Activity Library open the Machine Learning tab.

    Open Machine Learning tab
  3. On the Machine Learning tab, drag the Amazon Machine Learning activity onto your process.

    Drag Amazon Machine Learning activity

General Configuration

Specifies the basic settings for the Amazon Machine Learning activity.

Figure: General Configuration screen

General Configuration screen

Fields

Field Name Definition

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

Amazon Machine Learning Configuration > Request tab

Configures the score models for an activity where the Amazon Machine Learning model runs.

Figure: Amazon Machine Learning Configuration > Request tab

Amazon Machine Learning Configuration Request tab

Fields

Field Name Definition

Add Score Model Add Score Model icon

Function:
Creates a score model with a name you specify.

Edit Edit icon

Function:
Changes the selected item.

Delete Delete icon

Function:
Deletes the selected item.
Example:
Refer to:

Amazon Machine Learning

Function:
Specifies the access token that connects to your Amazon Machine Learning service.
Accepted Values:
A list of access tokens configured for your environment.
Default Value:
None
Accepts Process Data Variables:
No

Create Add Token icon

Opens this Screen:
Access Token for Amazon Web Services
Function of this Screen:
Configure an access token to connect to Amazon Web Services.

ML Model

Function:
Specifies the Amazon Machine Learning model name to use for predictions.

When you select the access token from the Amazon Machine Learning field, this field shows all your Amazon Machine Learning models.

Accepted Values:
The Amazon Machine Learning model from the list.
Default Value:
None
Limitations:

Some information about third-party integrations is outside the scope of the AgilePoint NX Product Documentation. It is the responsibility of the vendors who create and maintain these technologies to provide this information. This includes specific business use 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, or 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?

Activity

Function:
Specifies an activity on which to run the Amazon Machine Learning model.
Accepted Values:
An activity from the list.
Default Value:
None
Accepts Process Data Variables:
No

On Event

Function:
Specifies the activity event where the change occurs.
Accepted Values:
  • Assign Work Item - Amazon Machine Learning runs when a task is Assigned to a participant.
  • Complete Work Item - Amazon Machine Learning runs when a task is Completed.
  • Cancel Work Item - Amazon Machine Learning runs when a task is Cancelled.
  • Enter Activity Instance - Amazon Machine Learning runs when the activity starts.
  • Leave Activity Instance - Amazon Machine Learning runs when the the activity ends.
  • Reassign Work Item - Amazon Machine Learning runs when a task is Reassigned.
  • Work Item Assigned - Amazon Machine Learning runs when a task is Assigned to a participant.
  • Work Item Overdue - Amazon Machine Learning runs when a task is Overdue.
Default Value:
None

Request Mapping

Function:
Connects the eForm values to the Amazon Machine Learning model.
Accepted Values:
Click the Schema Mapping Schema Mapping icon 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. It is the responsibility of the vendors who create and maintain these technologies to provide this information. This includes specific business use 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, or 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?

Save

Opens this Screen:
Saves the configuration for your score model.

Amazon Machine Learning Configuration > Response tab

Specifies where to store the response from Amazon Machine Learning.

Figure: Amazon Machine Learning Configuration > Response tab

Amazon Machine Learning Configuration Response tab

Fields

Field Name Definition

Add Score Model Add Score Model icon

Function:
Creates a score model with a name you specify.

Edit Edit icon

Function:
Changes the selected item.

Delete Delete icon

Function:
Deletes the selected item.
Example:
Refer to:

Amazon Machine Learning

Function:
Specifies the access token that connects to your Amazon Machine Learning service.
Accepted Values:
A list of access tokens configured for your environment.
Default Value:
None
Accepts Process Data Variables:
No

Create Add Token icon

Opens this Screen:
Access Token for Amazon Web Services
Function of this Screen:
Configure an access token to connect to Amazon Web Services.

ML Model

Function:
Specifies the Amazon Machine Learning model name to use for predictions.

When you select the access token from the Amazon Machine Learning field, this field shows all your Amazon Machine Learning models.

Accepted Values:
The Amazon Machine Learning model from the list.
Default Value:
None
Limitations:

Some information about third-party integrations is outside the scope of the AgilePoint NX Product Documentation. It is the responsibility of the vendors who create and maintain these technologies to provide this information. This includes specific business use 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, or 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?

Activity

Function:
Specifies an activity on which to run the Amazon Machine Learning model.
Accepted Values:
An activity from the list.
Default Value:
None
Accepts Process Data Variables:
No

On Event

Function:
Specifies the activity event where the change occurs.
Accepted Values:
  • Assign Work Item - Amazon Machine Learning runs when a task is Assigned to a participant.
  • Complete Work Item - Amazon Machine Learning runs when a task is Completed.
  • Cancel Work Item - Amazon Machine Learning runs when a task is Cancelled.
  • Enter Activity Instance - Amazon Machine Learning runs when the activity starts.
  • Leave Activity Instance - Amazon Machine Learning runs when the the activity ends.
  • Reassign Work Item - Amazon Machine Learning runs when a task is Reassigned.
  • Work Item Assigned - Amazon Machine Learning runs when a task is Assigned to a participant.
  • Work Item Overdue - Amazon Machine Learning runs when a task is Overdue.
Default Value:
None

Store the Response in Custom Attribute / Map Response to AgilePoint Schema

Function:
Specifies where to store the data in the response from Amazon Machine Learning.
Accepted Values:
  • Store the Response in Custom Attribute - Select this option if you expect Amazon Machine Learning to return only one data item.

    In the text field, specify a variable to store the data Amazon Machine Learning returns.

  • Map Response to AgilePoint Schema - Select this option if you expect Amazon Machine Learning to return more than one data item.

    Click the Schema Mapping Schema Mapping icon button to open the Schema Mapper.

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

Default Value:
Map Response to AgilePoint Schema.

No default value is specified for the variable. You must select a variable, or map the response to your schema.

Accepts Process Data Variables:
  • If you select Store the Response in Custom Attribute, you must enter a variable.
  • If you select Map Response to AgilePoint Schema, this does not apply.
Limitations:

Some information about third-party integrations is outside the scope of the AgilePoint NX Product Documentation. It is the responsibility of the vendors who create and maintain these technologies to provide this information. This includes specific business use 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, or 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?

Save

Opens this Screen:
Saves the configuration for your score model.

Amazon Machine Learning Configuration > Additional Actions tab

Specifies whether to skip the activities in the AgilePoint process when specified conditions occur.

Figure: Amazon Machine Learning Configuration > Additional Actions tab

Amazon Machine Learning Configuration Additional Actions tab

Fields

Field Name Definition

Add Score Model Add Score Model icon

Function:
Creates a score model with a name you specify.

Edit Edit icon

Function:
Changes the selected item.

Delete Delete icon

Function:
Deletes the selected item.
Example:
Refer to:

Amazon Machine Learning

Function:
Specifies the access token that connects to your Amazon Machine Learning service.
Accepted Values:
A list of access tokens configured for your environment.
Default Value:
None
Accepts Process Data Variables:
No

Create Add Token icon

Opens this Screen:
Access Token for Amazon Web Services
Function of this Screen:
Configure an access token to connect to Amazon Web Services.

ML Model

Function:
Specifies the Amazon Machine Learning model name to use for predictions.

When you select the access token from the Amazon Machine Learning field, this field shows all your Amazon Machine Learning models.

Accepted Values:
The Amazon Machine Learning model from the list.
Default Value:
None
Limitations:

Some information about third-party integrations is outside the scope of the AgilePoint NX Product Documentation. It is the responsibility of the vendors who create and maintain these technologies to provide this information. This includes specific business use 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, or 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?

Activity

Function:
Specifies an activity on which to run the Amazon Machine Learning model.
Accepted Values:
An activity from the list.
Default Value:
None
Accepts Process Data Variables:
No

On Event

Function:
Specifies the activity event where the change occurs.
Accepted Values:
  • Assign Work Item - Amazon Machine Learning runs when a task is Assigned to a participant.
  • Complete Work Item - Amazon Machine Learning runs when a task is Completed.
  • Cancel Work Item - Amazon Machine Learning runs when a task is Cancelled.
  • Enter Activity Instance - Amazon Machine Learning runs when the activity starts.
  • Leave Activity Instance - Amazon Machine Learning runs when the the activity ends.
  • Reassign Work Item - Amazon Machine Learning runs when a task is Reassigned.
  • Work Item Assigned - Amazon Machine Learning runs when a task is Assigned to a participant.
  • Work Item Overdue - Amazon Machine Learning runs when a task is Overdue.
Default Value:
None

Change Flow

Function:
Specifies whether to skip the specified activities in the AgilePoint process after specific conditions occur.
Accepted Values:
  • Selected - Skips the specified activities in the AgilePoint process.
  • Deselected - Follows the standard process, and does not skip any activities.
Default Value:
Deselected

Configure Conditions

Opens this Screen:
Configure Conditions screen
To Open this Field:
  1. On the Additional Actions tab, click Change Flow.
Function of this Screen:
Specifies the conditions that cause the process to skip activities.

Save

Opens this Screen:
Saves the configuration for your score model.

Amazon Machine Learning Configuration > Configure Conditions screen

Specifies the conditions that cause the process to skip activities.

Figure: Amazon Machine Learning Configuration > Configure Conditions screen

Amazon Machine Learning Configuration Configure Conditions screen

Fields

Field Name Definition

Rule Type

Function:
Specifies a rule to execute.
Accepted Values:
  • IF - Specifies a rule to execute if a specified condition is true.
  • ELSE IF - Specifies a rule to execute if the previous condition is false.

    To open this field, click Add New Rule Add New Rule icon.

  • ELSE - The rule executes if the all the specified conditions are false.
Default Value:
  1. IF
  2. ELSE

Condition

Function:
Specifies a name for a rule in your condition.
Accepted Values:
One line of text that can have spaces.
Default Value:
Rule Name 1

Change Flow

Function:
Specifies the activity to skip in the AgilePoint process after specific conditions occur.

This field shows the activities in AgilePoint process.

Accepted Values:
An activity from the list.
Default Value:
Deselected

Configure Conditions Configure Conditions icon

Opens this Screen:
Condition Builder screen
Function of this Screen:
Creates or changes logical rules. You can put one statement inside another statement to create complex logical expressions.

Add New Rule Add New Rule icon

Function:
Lets you to add more than one rule.

Amazon Machine Learning Configuration > Condition Builder screen

Creates or changes logical rules. You can put one statement inside another statement to create complex logical expressions.

Figure: Amazon Machine Learning Configuration > Condition Builder screen

Amazon Machine Learning Configuration Condition Builder screen

Fields

Field Name Definition

Condition Name

Function:
Specifies a name for your rule.
Accepted Values:
Read only.
Default Value:
Rule Name 1

Validate Validate icon

Function:
Makes sure the rule is correct.

Preview Preview icon

Function:
Shows the preview of your rule.

Rule Variable

Function:
Specifies the value to analyze.
Accepted Values:
Default Value:
None
Accepts Process Data Variables:
Yes
Example:
Refer to:

Operator

Function:
Lets you select the operators for a logical expression.
Accepted Values:
Data Type Expression Operators

String

, ==, StartsWith, EndsWith, Contains, !=, Does Not Contain Data, Contains Data

Bool

==

Date Time

, ==, >, >= , <, <=, !=

Number

, ==, >, >=, <, <=, !=

Default Value:
None
Example:
Refer to:

Rule Value

Function:
The value for the data variable.
Accepted Values:
Default Value:
None
Accepts Process Data Variables:
Yes
Example:
Refer to:

Add Row Add Row icon

Function:
Specifies another expression that can be joined to previous expression using the logical AND or OR operator.
  • AND - Specifies the AND operator.
  • OR - Specifies the OR operator.

Indent Right Indent Right icon

Function:
Creates the statement that is a condition of a parent statement.

Delete Delete icon

Function:
Deletes the selected item.
Example:
Refer to:

Back Back icon

Function:
Saves your rule and goes back to the Condition Builder screen.