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
Old sources: nnet archive

Reverse dependencies:

Reverse depends: abc, BarcodingR, BART, bcROCsurface, CBPS, depmixS4, elect, epiDisplay, gamlss.add, gamlss.mx, HardyWeinberg, ModTools, nftbart, pocrm, sodavis, TBFmultinomial
Reverse imports: batchtma, BayesTree, BCClong, Biocomb, biomod2, bndovb, brglm2, car, CARRoT, CaseCohortCoxSurvival, causal.decomp, causalBatch, CausalMetaR, cemco, cfbfastR, chemmodlab, chemometrics, CIMTx, coca, CoImp, Compositional, CondCopulas, CORElearn, corHMM, cpfa, cpt, daltoolbox, DChaos, difNLR, diversityForest, DMLLZU, 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, kgschart, LCAvarsel, LDATS, 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, ProFAST, projpred, pRoloc, PSweight, qgcomp, radiant.model, rasclass, RaSEn, RBtest, RclusTool, RecordLinkage, regfilter, rgnoisefilt, rifi, rifiComparative, rminer, RRMLRfMC, RTextTools, rties, RVAideMemoire, scde, SDMtune, semiArtificial, seq2pathway, seqest, seqimpute, ShinyItemAnalysis, shinyr, SIDES, sigQC, simPop, SLCARE, SLEMI, soilassessment, sparsebnUtils, 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, plot3logit, pmml, probably, 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, margins, prediction, stargazer, texreg, vip

Linking:

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