SRBench: Symbolic Regression Benchmarks

The methods for symbolic regression (SR) have come a long way since the days of Koza-style genetic programming (GP). Our goal with this project is create a living benchmark of modern symbolic regression methods, in the context of state-of-the-art ML methods, and with a view towards high-impact applications in the health sciences.

Symbolic regression algorithms (marked with asterisk) benchmarked against black-box ML on hundreds of regression problems. La Cava et al. NeurIPS 2021
Symbolic regression algorithms (marked with asterisk) benchmarked against black-box ML on hundreds of regression problems. La Cava et al. NeurIPS 2021

Code

  • SRBench: A living Benchmark for Symbolic Regression

    • Selected Papers

    SRBench++: Principled Benchmarking of Symbolic Regression With Domain-Expert Interpretation
    F. O. de Franca, M. Virgolin, M. Kommenda, M. S. Majumder, M. Cranmer, G. Espada, L. Ingelse, A. Fonseca, M. Landajuela, B. Petersen, R. Glatt, N. Mundhenk, C. S. Lee, J. D. Hochhalter, D. L. Randall, P. Kamienny, H. Zhang, G. Dick, A. Simon, B. Burlacu, Jaan Kasak, Meera Machado, Casper Wilstrup, W. G. La Cava (2024)
    IEEE Transactions on Evolutionary Computation
    ieeexplore.ieee.org  |  arXiv  |  pdf  |  code
    Contemporary Symbolic Regression Methods and their Relative Performance
    William La Cava, Patryk Orzechowski, Bogdan Burlacu, Fabricio de Franca, Marco Virgolin, Ying Jin, Michael Kommenda, Jason Moore (2021)
    Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks
    datasets-benchmarks-proceedings.neurips.cc  |  arXiv  |  pdf  |  code
    A comparative study of GP-based and state-of-the-art classifiers on a synthetic machine learning benchmark
    Patryk Orzechowski, Paweł Renc, William La Cava, Jason H. Moore, Arkadiusz Sitek, Jaroslaw Wąs, Joost Wagenaar (2022)
    Proceedings of the Genetic and Evolutionary Computation Conference Companion
    dl.acm.org  |  pdf
    Where are we now? A large benchmark study of recent symbolic regression methods
    Patryk Orzechowski, William La Cava, Jason H. Moore (2018)
    Proceedings of the 2018 Genetic and Evolutionary Computation Conference
    dl.acm.org  |  arXiv  |  pdf
    Benchmarking in Optimization: Best Practice and Open Issues
    Thomas Bartz-Beielstein, Carola Doerr, Daan Berg, Jakob Bossek, Sowmya Chandrasekaran, Tome Eftimov, Andreas Fischbach, Pascal Kerschke, William La Cava, Manuel Lopez-Ibanez, Katherine M. Malan, Jason H. Moore, Boris Naujoks, Patryk Orzechowski, Vanessa Volz, Markus Wagner, Thomas Weise (2020)
    Preprint
    arxiv.org  |  pdf