1. Administration and Configuration Guide
  2. Use Cases
  3. Behavioral Model
  4. Batch Framework for Behavioral Model
  5. Behavioral Model Scoring

5.2.4.2 Behavioral Model Scoring

  • This pre-seeded batch will be available in all workspaces (Production and Sandboxes ).

    Note:

    This batch has to be executed in the Production workspace
Batch and Task Parameters
The batch contains the following tasks:
Task 1: Aggregate_Base_Features, Task Parameters
  • Objective folder for this task:
    Home / Modeling / Pipelines / ML4AML / Scenario Model / Batch / Base
Features

    Note:

    Do not change any parameter except Optional Parameters.
  • Optional Parameters:
    • prod_flag: Flag to indicate Training/Scoring scenario. The option is Y or N. For production/ scoring scenarios, the prod_flag should be set to Y.
    • model_group_name: Name of the Model Group for which Base Feature Aggregation is created. Example: LOB1.
    • model_name: Name of the Model used while importing the model template using Admin Notebook. Example: RMF.
    • focus: The model entity name is provided in the Admin notebook dataframe while creating the model group. The option is CUSTOMER or ACCOUNT.

      For example:

      prod_flag=Y,model_group_name=GROUP1,model_name=M1,focus=CUSTOMER

  • Edit Task Parameters and Save.

    Figure 5-27 Edit Task for SM Scoring


    Description of Figure 5-27 follows
    Description of "Figure 5-27 Edit Task for SM Scoring"

Task 2: ML_Scoring, Task Parameters
  • Objective folder for this task:
    Home / Modeling / Pipelines / ML4AML / Scenario Model / AIF

    Note:

    Do not change any parameter except Optional Parameters.
  • Optional Parameters:
    • btl_sample_count: Number of random samples below the cutoff that should be considered while scoring.
    • debug_flag: Used for debugging purposes only. By default, set it to False.
    • n_top_contrib: Top N features contributing to model score. By default, set it to None.

      For example: btl_sample_count=50,debug_flag=False,n_top_contrib=None

  • Edit Task Parameters and Save.

    Figure 5-28 Edit Task Parameter for ML Scoring


    Description of Figure 5-28 follows
    Description of "Figure 5-28 Edit Task Parameter for ML Scoring"

    Note:

    Once the batch execution is successful, the results are available in the SM_EVENT_SCORE and SM_EVENT_SCORE_DETAILS tables. For more information on these table structure, see the OFS Compliance Studio Data Model Reference Guide.
Task 3: Event_Processing Task Parameters
  • Objective folder for this task:
    Home / Modeling / Pipelines / ML4AML / Scenario Model / Batch / Event
Processing

    Note:

    Do not change any parameter except Optional Parameters.
  • Optional Parameters:
    • model_group_name: Name of the Model Group for which Base Feature Aggregation is created. Example: LOB1.
    • model_name: Name of the Model used while importing the model template using Admin Notebook. Example: RMF.
    • focus: The model entity name is provided in the Admin notebook dataframe while creating the model group. The option is CUSTOMER or ACCOUNT.

      For example: model_group_name=GROUP1,model_name=M1,focus=CUSTOMER

  • Edit Task Parameters and Save Task Parameters and Save

    Figure 5-29 Edit Task Parameter for Event Processing


    Description of Figure 5-29 follows
    Description of "Figure 5-29 Edit Task Parameter for Event Processing"

Task: Output Overlays

This is an optional task added manually for running the score update notebook with static logic to update scores generated by the ML Scoring task.

This new task will be placed after the ML_Scoring task and before the Event_Processing task in the SM_Scoring batch.

Note:

Prerequisites: See the Score Update Notebook for Scenario Model section in theOFS Compliance Studio Use Case Guide.

In the Production workspace, the score update notebook can be executed via batch framework.

For executing the score update notebook via batch framework, follow these steps:
  1. On the Orchestration mega menu, click Define Batch.
  2. Search SM_Scoring Batch, and clone the batch using the Copy icon. The Copy Batch page is displayed.

    Figure 5-30 Copy Batch


    Description of Figure 5-30 follows
    Description of "Figure 5-30 Copy Batch"

  3. Provide a new name to the batch and click Save.
  4. On the Orchestration mega menu, click Define Tasks and select the newly created batch.
  5. Copy any existing task using the Copy icon. The Copy Task page is displayed.

    Figure 5-31 Copy Task


    Description of Figure 5-31 follows
    Description of "Figure 5-31 Copy Task"

  6. Create a new task and provide the name as Score_Update.
  7. Select the Model parameter where the draft notebook is present.
  8. Click Save.
  9. After the new Task is created, use the Menu icon and adjust the Precedence Mapping of tasks.
  10. Place the new task after ML_Scoring and before Event_Processing tasks as shown below.

    Figure 5-32 Precedence Mapping


    Description of Figure 5-32 follows
    Description of "Figure 5-32 Precedence Mapping"

    Figure 5-33 Precedence


    Description of Figure 5-33 follows
    Description of "Figure 5-33 Precedence"

  11. On the Orchestration mega menu, click Schedule Batches.
  12. Select the newly created batch, provide the parameters for each task, and trigger the batch.

    The newly created task will pass the control to the new notebook.

    Figure 5-34 Event Score Update


    Description of Figure 5-34 follows
    Description of "Figure 5-34 Event Score Update"

    Note:

    The code in the new notebook will update the scores directly into the production table (SM_EVENT_SCORE_DETAILS). For more information on the table structure, see the OFS Compliance Studio Data Model Reference Guide.