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nnet: Feed-Forward Neural Networks and Multinomial Log-Linear Models

Software for feed-forward neural networks with a single hidden layer, and for multinomial log-linear models.

Version: 7.3-19
Priority: recommended
Depends: R (≥ 3.0.0), stats, utils
Suggests: MASS
Published: 2023-05-03
Author: Brian Ripley [aut, cre, cph], William Venables [cph]
Maintainer: Brian Ripley <ripley at stats.ox.ac.uk>
License: GPL-2 | GPL-3
URL: http://www.stats.ox.ac.uk/pub/MASS4/
NeedsCompilation: yes
Citation: nnet citation info
Materials: NEWS
In views: Econometrics, MachineLearning
CRAN checks: nnet results

Documentation:

Reference manual: nnet.pdf

Downloads:

Package source: nnet_7.3-19.tar.gz
Windows binaries: r-devel: nnet_7.3-19.zip, r-release: nnet_7.3-19.zip, r-oldrel: nnet_7.3-19.zip
macOS binaries: r-release (arm64): nnet_7.3-19.tgz, r-oldrel (arm64): nnet_7.3-19.tgz, r-release (x86_64): nnet_7.3-19.tgz, r-oldrel (x86_64): nnet_7.3-19.tgz
Old sources: nnet archive

Reverse dependencies:

Reverse depends: abc, BarcodingR, BART, bcROCsurface, CBPS, depmixS4, elect, epiDisplay, gamlss.add, gamlss.mx, HardyWeinberg, LearnPCA, ModTools, nftbart, pocrm, sodavis, TBFmultinomial
Reverse imports: batchtma, BayesTree, BCClong, biomod2, bndovb, brglm2, car, CARRoT, CaseCohortCoxSurvival, causal.decomp, causalBatch, CausalMetaR, cemco, chemmodlab, chemometrics, CIMTx, coca, CoImp, Compositional, CondCopulas, CORElearn, corHMM, cpfa, cpt, daltoolbox, DChaos, difNLR, diversityForest, drpop, DTRreg, EffectLiteR, effects, eglhmm, em, EnsembleBase, EpiForsk, EPX, ExactMed, factormodel, fdm2id, flexmix, forecast, Frames2, fRegression, GenMarkov, geomod, gesttools, gfoRmula, glm.predict, GLMpack, GMDH2, gnm, GPSCDF, gscaLCA, gspcr, gWQS, Hmisc, hmm.discnp, Hmsc, ImputeLongiCovs, ipred, ipw, IsingSampler, isni, ivitr, jmv, JSDNE, kgschart, LCAvarsel, LDATS, lmap, logisticRR, LUCIDus, MachineShop, MaOEA, matrixdist, mcca, mDAG, MEclustnet, MEDseq, mExplorer, mice, mixvlmc, mlearning, MNLR, Modeler, MoEClust, MSclassifR, multe, MXM, nempi, netZooR, NeuralNetTools, nlpsem, nnNorm, noisemodel, npcs, ODRF, ordinalForest, pemultinom, pheble, polyreg, poolABC, projpred, pRoloc, PSweight, qgcomp, radiant.model, rasclass, RaSEn, RBtest, RclusTool, RecordLinkage, rgnoisefilt, rifi, rifiComparative, RISCA, rminer, RRMLRfMC, RTextTools, rties, RVAideMemoire, scde, SDMtune, semiArtificial, seq2pathway, seqest, seqimpute, ShinyItemAnalysis, shinyr, SIDES, sigQC, simPop, SLCARE, SLEMI, soilassessment, spls, SSDM, synthpop, TheSFACE, traineR, translate.logit, tsDyn, TSPred, VIM, viraldomain, viralmodels, visualpred, VLMCX, WeightedCluster
Reverse suggests: adjustedCurves, AER, AICcmodavg, ALEPlot, analyzer, aplore3, baguette, BaM, bamlss, BiodiversityR, broom, broom.helpers, bruceR, buildmer, butcher, caret, caretEnsemble, catdata, causaldrf, cdgd, classmap, CLME, CMA, condvis2, cv, cvms, discSurv, DynTxRegime, e1071, evclass, evreg, ExplainPrediction, fable, familiar, FLAME, flowml, fscaret, GAparsimony, generalhoslem, GGally, ggeffects, ggstats, glmglrt, glmulti, gofcat, gtsummary, HandTill2001, hesim, hnp, huxtable, iBreakDown, insight, lda, marginaleffects, MASS, MatchIt, mboost, mclogit, mi, micd, MLInterfaces, mlogit, mlr, mlr3learners, mlrMBO, mlt, mlt.docreg, MNLpred, modelsummary, MuMIn, mvrsquared, nestedLogit, NeuralSens, ordinal, parameters, pdp, performanceEstimation, personalized, pmml, probably, ProFAST, psychomix, pubh, R2HTML, rattle, Rcmdr, RcmdrPlugin.NMBU, relimp, rms, ROSE, seqHMM, sharp, shipunov, sits, sjmisc, Sojourn.Data, sparklyr, sperrorest, sr, stablelearner, stacks, subsemble, SuperLearner, superMICE, tidyfit, validann, vcdExtra
Reverse enhances: emmeans, prediction, stargazer, texreg, vip

Linking:

Please use the canonical form https://CRAN.R-project.org/package=nnet to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.