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Encyclopedia of Machine Learning pp 327–330Cite as

Equation Discovery

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Synonyms

Computational discovery of quantitative laws; Symbolic regression

Definition

Equation discovery is a machine learning task that deals with the problem of learning quantitative laws and models, expressed in the form of equations, in collections of measured numeric data. Equation discovery methods take at input a data set consisting of measured values of a set of numeric variables of an observed system or phenomenon. At output, equation discovery methods provide a set of equations, such that, when used to calculate the values of system variables, the calculated values closely match the measured ones.

Motivation and Background

Equation discovery methods can be used to solve complex modeling tasks, i.e., establishing a mathematical model of an observed system. Modeling tasks are omnipresent in many scientific and engineering domains.

Equation discovery is strongly related to system identification, another approach to mathematical modeling. System identification methods work under...

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Authors and Affiliations

    Authors
    1. Ljupčo Todorovski
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    Editor information

    Editors and Affiliations

    1. School of Computer Science and Engineering, University of New South Wales, Sydney, Australia, 2052

      Claude Sammut

    2. Faculty of Information Technology, Clayton School of Information Technology, Monash University, P.O. Box 63, Victoria, Australia, 3800

      Geoffrey I. Webb

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    © 2011 Springer Science+Business Media, LLC

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    Todorovski, L. (2011). Equation Discovery. In: Sammut, C., Webb, G.I. (eds) Encyclopedia of Machine Learning. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-30164-8_258

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