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The documentation offers several entry points to the AutoML framework:

User-callable functions
To use the interface with no need for detailed information on implementation
Low-level introduction to procedures undertaken within the framework

Sections correspond to the core elements of most machine-learning workflows:

Advanced parameter modifications
To change underlying functionality using tunable parameters

Graphing structure

Version 0.3.0 of the AutoML framework has undergone fundamental changes with respect to the coding structure. In particular, the framework has moved from a small number of closely-dependent functions to a coding pattern which separates the individual pieces of required functionality into distinct sections. This is facilitated by the directed acyclic graph structure.

Understanding the structure provides insights into the functionality and their interdependencies. It also explains the documentation breakdown within the data pre-processing, data processing and data post-processing sections, which reference the applied functions within each of these sections based on their node within the graph i.e.


The following image fully describes the interconnection between sections of the framework.