ERFit: Entropic Regression Fit Matlab Package, for Data-Driven System Identification of Underlying Dynamic Equations
This provides a tool for researchers and engineers in science and engineering to perform system identification, but it is incremental as it packages an existing method into software.
The authors tackled the problem of data-driven sparse system identification for dynamic equations by developing ERFit, a MATLAB package based on entropic regression, which requires minimal supervision and adapts to various science and engineering problems.
Data-driven sparse system identification becomes the general framework for a wide range of problems in science and engineering. It is a problem of growing importance in applied machine learning and artificial intelligence algorithms. In this work, we developed the Entropic Regression Software Package (ERFit), a MATLAB package for sparse system identification using the entropic regression method. The code requires minimal supervision, with a wide range of options that make it adapt easily to different problems in science and engineering. The ERFit is available at https://github.com/almomaa/ERFit-Package