Glmnet in Matlab: Lasso and elastic-net regularized generalized linear models. This is a Matlab port for the efficient procedures for fitting the entire lasso or elastic-net path for linear regression, logistic and multinomial regression, Poisson regression and the Cox model. Features include: high efficiency by using coordinate descent with warm starts and active set iterations; methods for prediction, plotting and k-fold cross-validation; extensive options such as sparse input-matrix formats and range constraints on coefficients. Two recent additions are the multiresponse gaussian, and the grouped multinomial.

References in zbMATH (referenced in 11 articles )

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  1. Kim, Sun Hye; Boukouvala, Fani: Machine learning-based surrogate modeling for data-driven optimization: a comparison of subset selection for regression techniques (2020)
  2. Koo, Bonsoo; Anderson, Heather M.; Seo, Myung Hwan; Yao, Wenying: High-dimensional predictive regression in the presence of cointegration (2020)
  3. Takahashi, Takashi; Kabashima, Yoshiyuki: Semi-analytic approximate stability selection for correlated data in generalized linear models (2020)
  4. Zhang, Chunxia; Wu, Yilei; Zhu, Mu: Pruning variable selection ensembles (2019)
  5. Bien, Jacob; Gaynanova, Irina; Lederer, Johannes; Müller, Christian L.: Non-convex global minimization and false discovery rate control for the TREX (2018)
  6. Karl Sjöstrand; Line Clemmensen; Rasmus Larsen; Gudmundur Einarsson; Bjarne Ersbøll: SpaSM: A MATLAB Toolbox for Sparse Statistical Modeling (2018) not zbMATH
  7. Viola, Marco; Sangiovanni, Mara; Toraldo, Gerardo; Guarracino, Mario R.: A generalized eigenvalues classifier with embedded feature selection (2017)
  8. Michoel, Tom: Natural coordinate descent algorithm for (\ell_1)-penalised regression in generalised linear models (2016)
  9. Wehbe, Leila; Ramdas, Aaditya; Steorts, Rebecca C.; Shalizi, Cosma Rohilla: Regularized brain reading with shrinkage and smoothing (2015)
  10. Srivastava, Ashok N.: Greener aviation with virtual sensors: a case study (2012) ioport
  11. Jerome Friedman; Trevor Hastie; Rob Tibshirani: Regularization Paths for Generalized Linear Models via Coordinate Descent (2010) not zbMATH