IEEE Systems, Man and Cybernetics Magazine - April 2021 - 13

©SHUTTERSTOCK.COM/CONO0430

The Universal
Functions
Originator and
Its Extensions
Can They Solve the
Explanation Issue in Modern
Machine Learning
Applications?
by Ali R. Al-Roomi

Digital Object Identifier 10.1109/MSMC.2020.3036365
Date of current version: 20 April 2021

2333-942X/21©2021IEEE

	

M

odern machine learning (ML) tools, such
as artificial neural networks (ANNs) and
support vector machines (SVMs), can
provide highly accurate/precise predictions and estimations. However, in terms
of explainability and interpretability, they are poor. To
compromise between these key performance criteria, symbolic regression (SR) techniques could be used. However,
they are hard to program because they have complicated
mechanisms and need special optimization algorithms.
The universal functions originator (UFO) is a new ML computing system that can be used in many computationbased applications. In addition to describing the variability
of data sets as pure mathematical equations, this unique
Ap ri l 2021

IEEE SYSTEMS, MAN, & CYBERNETICS MAGAZINE	

13


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IEEE Systems, Man and Cybernetics Magazine - April 2021

Table of Contents for the Digital Edition of IEEE Systems, Man and Cybernetics Magazine - April 2021

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IEEE Systems, Man and Cybernetics Magazine - April 2021 - Cover1
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IEEE Systems, Man and Cybernetics Magazine - April 2021 - contents
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IEEE Systems, Man and Cybernetics Magazine - April 2021 - Cover3
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