3.6 ML4AML Use Case
This section describes the post-installation steps for ML4AML use case.
- Execute the following scripts.
importWorkspaceSQL.sh
importNotebooksSM.sh
importNotebooksASC.sh
importNotebooksAIF.sh
importNotebooksAMLES.sh
Note:
- Import the notebook based on your preferences.
- To import a workspace and notebook, see the Importing Workspace Metadata section in the OFS Compliance Studio Administration and Configuration Guide.
- For new model development, users
need to start with the Admin notebook CS 8.1.2.9.0 and then proceed with the model
training and scoring process.
To create a model, train, and score, see the OFS Compliance Studio Use Case Guide.
- To execute older notebooks, the
user needs to select the previous version of the Conda environment (CS 8.1.2.8.0) and run
the batches.
For Model Scoring/Annual Model Validation, see the How to Execute Model Scoring/Annual Model Validation with the Batch Framework section in the OFS Compliance Studio Administration and Configuration Guide.
For Monthly Model Validation, see the How to Execute Monthly Model Validation with the Batch Framework section in the OFS Compliance Studio Administration and Configuration Guide.
Scenario Conversion Utility (SCU)
- Execute the following scripts.
importWorkspaceSQLSCU.sh
importNotebooksSCU.sh
- Refresh the Materialized view.
- Generate Scenario and Threshold
notebook.
For more information, see the Using Scenario Conversion Utility for ASC section in the OFS Compliance Studio Administration and Configuration Guide.
Automated Scenario Calibration (ASC)
- Run the Scenario Conversion Utility.
- Create a threshold sets using bulk upload. For more information, see How to Upload Thresholds in Bulk for ASC section in the OFS Compliance Studio Use Case Guide.
- Create new ASC Definition. For more information, see the Automated Scenario Calibration (ASC) section in the OFS Compliance Studio Use Case Guide.
Note:
This patch will create backups of the affected jars, files, and directories, storing them in a backup folder.