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: 7.3-16
Priority: recommended
Depends: R (≥ 3.0.0), stats, utils
Suggests: MASS
Published: 2021-05-03
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, SocialSciences
CRAN checks: nnet results

Downloads:

Reference manual: nnet.pdf
Package source: nnet_7.3-16.tar.gz
Windows binaries: r-devel: nnet_7.3-16.zip, r-release: nnet_7.3-16.zip, r-oldrel: nnet_7.3-16.zip
macOS binaries: r-release (arm64): nnet_7.3-16.tgz, r-release (x86_64): nnet_7.3-16.tgz, r-oldrel: nnet_7.3-16.tgz
Old sources: nnet archive

Reverse dependencies:

Reverse depends: abc, abn, BarcodingR, BART, bcROCsurface, CBPS, dave, depmixS4, elect, epiDisplay, fdm2id, gamlss.add, gamlss.mx, gfmR, HIest, HydeNet, introgress, LOGICOIL, ModTools, partialOR, pocrm, sodavis, SQB, TBFmultinomial
Reverse imports: BaBooN, BayesTree, Biocomb, biomod2, bndovb, brglm2, car, CARRoT, causal.decomp, chemmodlab, chemometrics, CIMTx, coca, CoImp, Compositional, CORElearn, corHMM, cpt, DAMisc, DChaos, difNLR, diversityForest, DMLLZU, drhur, drpop, EffectLiteR, effects, EnsembleBase, EPX, expose, factormodel, factorplot, flexmix, forecast, Frames2, fRegression, GDAtools, gencve, gesttools, gfoRmula, glm.predict, glmdisc, GLMpack, GMDH2, gnm, GPSCDF, gscaLCA, gWQS, hmi, Hmisc, hmm.discnp, Hmsc, hybridEnsemble, ipred, ipw, IsingSampler, isni, ivitr, jmv, kgschart, landmap, LCAvarsel, LDATS, logisticRR, LUCIDus, MachineShop, MaOEA, mcca, mDAG, MEclustnet, MEDseq, mExplorer, mlearning, MNLR, Modeler, MoEClust, MXM, nempi, networktools, NeuralNetTools, nnNorm, nntrf, NoiseFiltersR, ordinalForest, Plasmode, polyreg, pRoloc, PropensitySub, PSweight, pvsR, radiant.model, rasclass, RaSEn, RBtest, RclusTool, RecordLinkage, RISCA, rminer, RRMLRfMC, RTextTools, rties, RVAideMemoire, scde, SDMtune, semiArtificial, seq2pathway, seqest, ShinyItemAnalysis, SIDES, sigQC, simPop, SLEMI, soilassessment, Sojourn, sparsebnUtils, spls, SSDM, synthpop, traineR, tsDyn, TSPred, VIM, visualpred
Reverse suggests: AER, AICcmodavg, ALEPlot, analyzer, aplore3, BaM, bamlss, BiodiversityR, boostr, broom, broom.helpers, bruceR, buildmer, butcher, caret, caretEnsemble, catdata, causaldrf, clarkeTest, classmap, CLME, CMA, condvis2, cvam, cvms, discSurv, DynTxRegime, e1071, ExplainPrediction, fable, fscaret, GAparsimony, generalhoslem, GGally, glmglrt, glmulti, gtsummary, HandTill2001, hesim, hnp, huxtable, iBreakDown, insight, lda, marginaleffects, MASS, MatchIt, mboost, mclogit, mi, mice, MLInterfaces, mlogit, mlr, mlr3learners, mlrMBO, mlt, mlt.docreg, MNLpred, modelplotr, modelsummary, MuMIn, mvrsquared, NeuralSens, nnetpredint, ordinal, pdp, performanceEstimation, personalized, plot3logit, pmml, psychomix, pubh, R2HTML, rattle, rbart, rbooster, Rcmdr, RcmdrPlugin.IPSUR, RcmdrPlugin.NMBU, RcmdrPlugin.pointG, relimp, ROSE, seqHMM, shipunov, Sojourn.Data, sparklyr, sperrorest, stablelearner, stacks, SuperLearner, validann, vcdExtra, vip
Reverse enhances: emmeans, margins, prediction, stargazer, texreg

Linking:

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