Pyglmnet: Python implementation of elastic-net regularized generalized linear models

Python Submitted 26 November 2019 • Published 01 March 2020
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Authors

Mainak Jas (0000-0002-3199-9027), Titipat Achakulvisut (0000-0002-2124-2979), Aid Idrizović, Daniel Acuna, Matthew Antalek, Vinicius Marques, Tommy Odland, Ravi Prakash Garg, Mayank Agrawal, Yu Umegaki, Peter Foley (0000-0002-0304-7213), Hugo Fernandes (0000-0002-0168-4104), Drew Harris, Beibin Li, Olivier Pieters (0000-0002-5473-4849), Scott Otterson, Giovanni De Toni (0000-0002-8387-9983), Chris Rodgers (0000-0003-1762-3450), Eva Dyer, Matti Hamalainen, Konrad Kording, Pavan Ramkumar (0000-0001-7450-0727)

Citation

Jas et al., (2020). Pyglmnet: Python implementation of elastic-net regularized generalized linear models. Journal of Open Source Software, 5(47), 1959, https://doi.org/10.21105/joss.01959

@article{Jas2020, doi = {10.21105/joss.01959}, url = {https://doi.org/10.21105/joss.01959}, year = {2020}, publisher = {The Open Journal}, volume = {5}, number = {47}, pages = {1959}, author = {Mainak Jas and Titipat Achakulvisut and Aid Idrizović and Daniel Acuna and Matthew Antalek and Vinicius Marques and Tommy Odland and Ravi Prakash Garg and Mayank Agrawal and Yu Umegaki and Peter Foley and Hugo Fernandes and Drew Harris and Beibin Li and Olivier Pieters and Scott Otterson and Giovanni De Toni and Chris Rodgers and Eva Dyer and Matti Hamalainen and Konrad Kording and Pavan Ramkumar}, title = {Pyglmnet: Python implementation of elastic-net regularized generalized linear models}, journal = {Journal of Open Source Software} }
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glm machine-learning lasso elastic-net group-lasso

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