Subclasses of Class Function used to Implement Transformations of Statistical Models

TL;DR

This paper introduces subclasses of class Function within a software library to facilitate transformations of statistical models, enhancing object-oriented and mathematical properties for machine learning applications.

Contribution

It defines specific subclasses of Function for model transformations, integrating them into an existing MML-guided inference library.

Findings

Implemented subclasses enable effective model transformations.

Enhanced the library's capabilities for statistical inference.

Supports better object-oriented design in statistical modeling.

Abstract

A library of software for inductive inference guided by the Minimum Message Length (MML) principle was created previously. It contains various (object-oriented-) classes and subclasses of statistical Model and can be used to infer Models from given data sets in machine learning problems. Here transformations of statistical Models are considered and implemented within the library so as to have desirable properties from the object-oriented programming and mathematical points of view. The subclasses of class Function needed to do such transformations are defined.