Incorporating background knowledge in symbolic regression using a computer algebra system

Incorporating background knowledge in symbolic regression using a computer algebra system

Symbolic regression (SR) can generate interpretable, concise expressions that fit a given dataset, allowing for more human understanding of the structure than black-box approaches. The addition of background knowledge (in the form of symbolic mathematical constraints) allows for the generation of ex...

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Bibliographic Details
Main Authors: Charles Fox, Neil D Tran, F Nikki Nacion, Samiha Sharlin, Tyler R Josephson
Format: Article
Language:English
Published: IOP Publishing 2024-01-01
Series:Machine Learning: Science and Technology
Subjects:
adsorption
symbolic regression
genetic algorithms
Bayesian
Online Access:https://doi.org/10.1088/2632-2153/ad4a1e

Internet

https://doi.org/10.1088/2632-2153/ad4a1e

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