What is it about?
Symbolic regression is a potential ML tool to infer mathematical equations directly from data. It is a primary form of interpretable ML as it learns fully transparent models. This tutorial paper introduces symbolic regression, discusses its main successes and presents its key limitations.
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Why is it important?
Symbolic regression is very useful in all domains and its application is likely to grow in the future. This articles help understanding, through simple language and examples, how it works using different ML-based approaches.
Perspectives
This tutorial paper summarizes all you need to know about symbolic regression. The main goal is to explain this ML tool, and invite researchers to deploy it in any application that requires learning a model from data with full transparency.
Nour Makke
Read the Original
This page is a summary of: Symbolic Regression: A Pathway to Interpretability Towards Automated Scientific Discovery, August 2024, ACM (Association for Computing Machinery),
DOI: 10.1145/3637528.3671464.
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