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.

Configure the Amazon Machine Learning activity

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

Prerequisites

AgilePoint NX OnDemand (public cloud), or AgilePoint NX PrivateCloud or AgilePoint NX OnPremises v7.0 Software Update 1 or higher.

Good to Know

To send an email notification, click Advanced > Email Notifications .
For more information, refer to Email Notifications screen (Process Activities).
In most text fields, you can use process data variables as an alternative to literal data values.
You can configure whether this activity waits for other activities before it runs.
For more information, refer to How Do I Configure an Activity to Wait for Other Incoming Activities?
This section shows the configuration settings on the configuration screens for this activity. Other configuration settings apply to system activities. For more information, refer to:
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?

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

Open Process Builder.
For information about how to open this screen, refer to Process Builder.
In Process Builder, in the Activity Library open the Machine Learning tab.
On the Machine Learning tab, drag the Amazon Machine Learning activity onto your process.

General Configuration

Specifies the basic settings for the Amazon Machine Learning activity.

Good to Know

Documentation for this screen is provided for completeness. The fields are mostly self-explanatory.

Fields

Field Name	Definition
Display Name	Description: Specifies the activity name that shows in your process. Allowed Values: One line of text (a string). Accepted: Letters Numbers Spaces Default Value: None Accepts 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	Description: Specifies an optional text description for your activity. Allowed Values: More than one line of text. Default Value: None Accepts Variables: No

Field Name

Definition

Display Name

Description:

Specifies the activity name that shows in your process.

Allowed Values:

One line of text (a string).

Accepted:

Letters
Numbers
Spaces

Default Value:

None

Accepts Variables:

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

Description:: Specifies an optional text description for your activity.
Allowed Values:: More than one line of text.
Default Value:: None
Accepts Variables:: No

Amazon Machine Learning Configuration > Request tab

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

Fields

Field Name	Definition
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
Amazon Machine Learning	Description: Specifies the access token that connects to your Amazon Machine Learning service. Allowed Values: A list of access tokens configured for your environment. Default Value: None Accepts Variables: No
Create	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	Description: 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. Allowed 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	Description: Specifies an activity on which to run the Amazon Machine Learning model. Allowed Values: An activity from the list. Default Value: None Accepts Variables: No
On Event	Description: Specifies the activity event where the change occurs. Allowed 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	Description: Connects the eForm values to the Amazon Machine Learning model. Allowed 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 Example: Refer to: (Example) Schema Mapper
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.

Fields

Field Name	Definition
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
Amazon Machine Learning	Description: Specifies the access token that connects to your Amazon Machine Learning service. Allowed Values: A list of access tokens configured for your environment. Default Value: None Accepts Variables: No
Create	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	Description: 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. Allowed 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	Description: Specifies an activity on which to run the Amazon Machine Learning model. Allowed Values: An activity from the list. Default Value: None Accepts Variables: No
On Event	Description: Specifies the activity event where the change occurs. Allowed 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	Description: Specifies where to store the data in the response from Amazon Machine Learning. Allowed 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 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 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.

Fields

Field Name	Definition
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
Amazon Machine Learning	Description: Specifies the access token that connects to your Amazon Machine Learning service. Allowed Values: A list of access tokens configured for your environment. Default Value: None Accepts Variables: No
Create	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	Description: 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. Allowed 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	Description: Specifies an activity on which to run the Amazon Machine Learning model. Allowed Values: An activity from the list. Default Value: None Accepts Variables: No
On Event	Description: Specifies the activity event where the change occurs. Allowed 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	Description: Specifies whether to skip the specified activities in the AgilePoint process after specific conditions occur. Allowed 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: 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.

Fields

Field Name	Definition
Rule Type	Description: Specifies a rule to execute. Allowed 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 . ELSE - The rule executes if the all the specified conditions are false. Default Value: IF ELSE
Condition	Description: Specifies a name for a rule in your condition. Allowed Values: One line of text (a string). Accepted: Letters Numbers Spaces Default Value: Rule Name 1
Change Flow	Description: Specifies the activity to skip in the AgilePoint process after specific conditions occur. This field shows the activities in AgilePoint process. Allowed Values: An activity from the list. Default Value: Deselected
Configure Conditions	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	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.

Fields

Field Name

Definition

Condition Name

Description:: Shows the name for your rule.
Allowed 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

Description:

Specifies the value to analyze.

Allowed Values:

One line of text (a string).

Accepted:

Letters
Numbers
Spaces

Default Value:

None

Accepts Variables:

Yes

Example:

Refer to:

(Example) Configure a Condition Activity (Check Leave Approval Status)

Operator

Description:

Lets you select the operators for a logical expression.

Allowed Values:

Data Type	Expression Operators
String	, ==, Starts with, Ends with, Contains, Does Not Contains, !=, Does Not Contain Data, Contains Data
Bool	==
Date Time	, ==, >, >= , <, <=, !=
Number	, ==, >, >=, <, <=, !=

Default Value:

None

Example:

Refer to:

Rule Value

Description:

The value for the data variable.

Allowed Values:

One line of text (a string).

Accepted:

Letters
Numbers
Spaces

Default Value:

None

Accepts Variables:

Yes

Example:

Refer to:

Add Row

Function:: Adds a row for the Field Name and Field Value.

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:

The videos on this page

Back Back icon

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