Training of Neural Networks

Training of neural networks using backpropagation, resilient backpropagation with (Riedmiller, 1994) or without weight backtracking (Riedmiller and Braun, 1993) or the modified globally convergent version by Anastasiadis et al. (2005). The package allows flexible settings through custom-choice of error and activation function. Furthermore, the calculation of generalized weights (Intrator O & Intrator N, 1993) is implemented.


Reference manual

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install.packages("neuralnet")

1.44.2 by Marvin N. Wright, 8 years ago


https://github.com/bips-hb/neuralnet


Report a bug at https://github.com/bips-hb/neuralnet/issues


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


Authors: Stefan Fritsch [aut] , Frauke Guenther [aut] , Marvin N. Wright [aut, cre] , Marc Suling [ctb] , Sebastian M. Mueller [ctb]


Documentation:   PDF Manual  


GPL (>= 2) license


Imports grid, MASS, grDevices, stats, utils, Deriv

Suggests testthat


Imported by AriGaMyANNSVR, CEEMDANML, ConvertPar, DeepLearningCausal, FRI, FWRGB, ImNN, Imneuron, LilRhino, Modeler, RSDA, SignacX, WaveST, WaveletML, nnfor, reddPrec, trackdem, traineR.

Depended on by MARSANNhybrid, quarrint.

Suggested by NeuralNetTools, NeuralSens, TrafficBDE, gemR, innsight, mcboost, misspi, mlr, plotmo, qeML.


See at CRAN