Amazon 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

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

Add Token

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, 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?

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 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?

Save

Opens this Screen:

Saves the configuration for your score model.

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

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

Add Token

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, 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?

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 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, 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?

Save

Opens this Screen:

Saves the configuration for your score model.

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

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

Add Token

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, 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?

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.

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 .

• 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

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.

Condition Name

Function:

Specifies a name for your rule.

Accepted Values:

Read only.

Default Value:

Rule Name 1

Validate

Function:

Makes sure the rule is correct.

Preview

Function:

Shows the preview of your rule.

Rule Variable

Function:

Specifies the value to analyze.

Accepted Values:

• One line of text that can have spaces.
• A process data variable.

Default Value:

None

Accepts Process Data Variables:

Yes

Example:

Refer to:

• (Example) Configure a Condition Activity to Check the Leave Approval Status in the Absence Request Process

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:

• (Example) Configure a Condition Activity to Check the Leave Approval Status in the Absence Request Process
• (Example) Configure a Condition Activity to Check the Leave Hours Available in the Absence Request Process

Rule Value

Function:

The value for the data variable.

Accepted Values:

• A text string that can have spaces.
• A process data variable.

Default Value:

None

Accepts Process Data Variables:

Yes

Example:

Refer to:

• (Example) Configure a Condition Activity to Check the Leave Approval Status in the Absence Request Process

Add

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.

Subcondition

Function:

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

Delete

Function:

Deletes the selected item.

Example:

Refer to:

• The videos on this page

Back

Function:

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