• SparseLOGREG

  • Referenced in 24 articles [sw11449]
  • Efficient Algorithm for Gene Selection using Sparse Logistic Regression. Motivation: This paper gives ... efficient algorithm for the sparse logistic regression problem. The proposed algorithm is based...
  • SINDy

  • Referenced in 15 articles [sw30277]
  • Constrained sparse Galerkin regression. The sparse identification of nonlinear dynamics (SINDy) is a recently proposed ... data-driven modelling framework that uses sparse regression techniques to identify nonlinear low-order models ... measurement data and satisfies necessary constraints. Galerkin regression models also readily generalize to include higher ... entire code base for our constrained sparse Galerkin regression algorithm is freely available online...
  • ARock

  • Referenced in 19 articles [sw16800]
  • decentralized consensus problems. Numerical experiments solving sparse logistic regression problems are presented...
  • LIBLINEAR

  • Referenced in 126 articles [sw04880]
  • large-scale linear classification. It supports logistic regression and linear support vector machines. We provide ... that LIBLINEAR is very efficient on large sparse data sets...
  • TIGRESS

  • Referenced in 9 articles [sw23826]
  • formulate GRN inference as a sparse regression problem and investigate the performance of a popular...
  • msgl

  • Referenced in 10 articles [sw26552]
  • Multinomial Sparse Group Lasso. Multinomial logistic regression with sparse group lasso penalty. Simultaneous feature selection...
  • spls

  • Referenced in 10 articles [sw09507]
  • package spls: Sparse Partial Least Squares (SPLS) Regression and Classification. This package ... provides functions for fitting a Sparse Partial Least Squares Regression and Classification...
  • SVMlight

  • Referenced in 257 articles [sw04076]
  • pattern recognition, for the problem of regression, and for the problem of learning a ranking ... applications. Many tasks have the property of sparse instance vectors. This implementation makes...
  • OOQP

  • Referenced in 36 articles [sw04743]
  • including general sparse QPs, QPs arising from support vector machines, Huber regression problems...
  • robustHD

  • Referenced in 4 articles [sw14244]
  • based on least angle regression and sparse regression...
  • camel

  • Referenced in 7 articles [sw14318]
  • linear models; (2) Calibrated Multivariate Regression for estimating sparse multivariate linear models; (3) Tiger, Calibrated...
  • SpaSM

  • Referenced in 4 articles [sw23903]
  • Matlab toolbox for performing sparse regression, classification and principal component analysis. The toolbox has been...
  • flare

  • Referenced in 17 articles [sw12406]
  • flare: Family of Lasso Regression. The package ”flare” provides the implementation of a family ... Lasso, Lq Lasso for estimating high dimensional sparse linear model. We adopt the alternating direction...
  • cobs

  • Referenced in 6 articles [sw21863]
  • cobs: Constrained B-Splines (Sparse Matrix Based). Qualitatively Constrained (Regression) Smoothing Splines via Linear Programming...
  • SOFAR

  • Referenced in 3 articles [sw31665]
  • suggest the method of sparse orthogonal factor regression (SOFAR) via the sparse singular value decomposition...
  • mixOmics

  • Referenced in 21 articles [sw09508]
  • highly dimensional data sets: regularized CCA and sparse PLS to unravel relationships between two heterogeneous ... step procedure and two frameworks are proposed: regression and canonical analysis. Numerous graphical outputs ... interpreting the results. Recent methodological developments include: sparse PLS-Discriminant Analysis, Independent Principal Component Analysis...
  • scalreg

  • Referenced in 1 article [sw25027]
  • package scalreg: Scaled sparse linear regression. Algorithms for fitting scaled sparse linear regression and estimating...
  • spcr

  • Referenced in 1 article [sw33155]
  • package spcr: Sparse Principal Component Regression. The sparse principal component regression is computed. The regularization...
  • PySINDy

  • Referenced in 1 article [sw33019]
  • systems from data. PySINDy is a sparse regression package with several implementations for the Sparse...
  • HCmodelSets

  • Referenced in 1 article [sw28001]
  • package HCmodelSets: Regression with a Large Number of Potential Explanatory Variables. Software for performing ... /pnas.1703764114> for sparse regression when the number of potential explanatory variables far exceeds the sample...