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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Todorovski, L. (2017). Equation Discovery. In: Sammut, C., Webb, G.I. (eds) Encyclopedia of Machine Learning and Data Mining. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-7687-1_258
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DOI: https://doi.org/10.1007/978-1-4899-7687-1_258
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