.. _overview:

Overview
========
ML4AML is a Machine Learning Module within Compliance Studio that has been tailored to address specific use cases in the AML domain using ML4AML APIs.

Module Hierarchy
----------------
The following figure illustrates the approach that is used for modularizing the ML4AML module.

.. figure:: ../images/module_hierarchy.png
   :scale: 50%
   :alt: ML4AML Module Hierarchy
   :align: center

ML4AML Modules
==============
The module implements user interface API’s for all the possible Machine Learning (ML) operations. Here are the details:

* **aif**: This class implements user interface API’s for ML.
* **aif_utility**: The utility class contains reusable components that interacts with Compliance Studio.
* **amles**: The amles class is a special use case of supervised learning for anti-money laundering for event scoring (AMLES).
* **supervised**: The supervised class contain methods required for supervised learning. It inherits methods from the aif and aif_utility classes.
* **unsupervised**: The unsupervised class contain methods required for the customer segmentation usecase. It inherits methods from the aif class.