Modern sparse linear regression
Project description
sparsereg is a collection of modern sparse (regularized) linear regression algorithms.
Implemented algorithms
Mcconaghy, T. (2011). FFX: Fast, Scalable, Deterministic Symbolic Regression Technology. Genetic Programming Theory and Practice IX, 235-260. DOI: 10.1007/978-1-4614-1770-5_13
Brunton, Steven L., Joshua L. Proctor, and J. Nathan Kutz. “Discovering governing equations from data by sparse identification of nonlinear dynamical systems.” Proceedings of the National Academy of Sciences 113.15 (2016): 3932-3937. DOI: 10.1073/pnas.1517384113
Bouchard, Kristofer E. “Bootstrapped Adaptive Threshold Selection for Statistical Model Selection and Estimation.” arXiv preprint arXiv:1505.03511 (2015).
Installation
pip install sparsereg
Project details
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