Lasso and Elastic-Net Regularized Generalized Linear Models

Extremely efficient procedures for fitting the entire lasso or elastic-net regularization path for linear regression, logistic and multinomial regression models, Poisson regression and the Cox model. Two recent additions are the multiple-response Gaussian, and the grouped multinomial regression. The algorithm uses cyclical coordinate descent in a path-wise fashion, as described in the paper linked to via the URL below.


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Reference manual

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install.packages("glmnet")

2.0-16 by Trevor Hastie, 3 months ago


http://www.jstatsoft.org/v33/i01/.


Browse source code at https://github.com/cran/glmnet


Authors: Jerome Friedman [aut, cre], Trevor Hastie [aut, cre], Rob Tibshirani [aut, cre], Noah Simon [aut, ctb], Balasubramanian Narasimhan [ctb], Junyang Qian [ctb]


Documentation:   PDF Manual  


Task views: Machine Learning & Statistical Learning, Survival Analysis


GPL-2 license


Imports methods

Depends on Matrix, utils, foreach

Suggests survival, knitr, lars


Imported by ArCo, BAYESDEF, BeSS, BootValidation, CISE, Causata, ComICS, CorReg, CovSelHigh, DMRnet, DWLasso, EnsembleBase, EnsemblePenReg, FADA, FindIt, GMDH2, GWLelast, HDCI, HiCblock, HiCglmi, IsingFit, LPR, LassoSIR, MESS, MFKnockoffs, MRFA, MWRidge, NCutYX, OHPL, PDN, PhylogeneticEM, RCPmod, RNAseqNet, RPtests, RSDA, RTextTools, SIS, SISIR, SOIL, SentimentAnalysis, SubgrpID, SurvRank, TANDEM, TVsMiss, XMRF, anoint, aurelius, bastah, bestglm, blkbox, c060, cocoreg, cpt, customizedTraining, dnr, eNetXplorer, ePCR, elasticIsing, enetLTS, episode, eshrink, expandFunctions, fuser, gamreg, gencve, glmnetUtils, graphicalVAR, hdi, hdm, hdme, hdnom, hit, hybridEnsemble, iml, imputeR, kernDeepStackNet, knockoff, lime, lmmen, lori, mRchmadness, mase, maxnet, mdpeer, metafuse, mgm, milr, mpath, mplot, msaenet, msr, natural, nnfor, nproc, pact, palasso, parboost, partialCI, pgraph, politeness, polywog, pre, prioritylasso, rarhsmm, regnet, rminer, rolypoly, rrpack, sentometrics, slimrec, sparsereg, sparsevar, stm, tsensembler.

Depended on by AdapEnetClass, BigTSP, BioMark, CAM, CBPS, DTRlearn, DivMelt, EstHer, Grace, HiCfeat, IGG, InvariantCausalPrediction, Lavash, MIRL, MMMS, MMS, MNS, MultiVarSel, PAS, PRIMsrc, RVtests, SIMMS, SparseLearner, SubLasso, TSGSIS, bapred, cosso, covTest, ctmle, elasso, fcd, glmnetcr, glmtlp, glmvsd, hdlm, ipflasso, lassoscore, mcen, mht, mmabig, netgsa, parcor, personalized, prototest, qut, refund.wave, regsel, relaxnet, roccv, selectiveInference, widenet.

Suggested by BiodiversityR, CBDA, CompareCausalNetworks, EBglmnet, EHR, FRESA.CAD, FeatureHashing, GWASinlps, LSAmitR, ModelGood, NAM, SPreFuGED, STPGA, SemiSupervised, SuperLearner, bWGR, bamlss, broom, caretEnsemble, catdata, ck37r, coefplot, eclust, emil, ensembleEN, fbRanks, flexmix, formulize, fscaret, ggfortify, heuristica, live, medflex, mlr, nscancor, ordinalNet, plotmo, pmml, projpred, pulsar, randomForestSRC, regsem, sAIC, simputation, simulator, sparklyr, sqlscore, stabs, subsemble, text2vec, varbvs, vimp, vip.

Enhanced by prediction.


See at CRAN