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.

Author | Stefan Fritsch [aut], Frauke Guenther [aut, cre], Marc Suling [ctb], Sebastian M. Mueller [ctb] |

Date of publication | 2016-08-16 12:08:44 |

Maintainer | Frauke Guenther <guenther@leibniz-bips.de> |

License | GPL (>= 2) |

Version | 1.33 |

**compute:** Computation of a given neural network for given covariate...

**confidence.interval:** Calculates confidence intervals of the weights

**gwplot:** Plot method for generalized weights

**neuralnet:** Training of neural networks

**neuralnet-package:** Training of Neural Networks

**plot.nn:** Plot method for neural networks

**prediction:** Summarizes the output of the neural network, the data and the...

neuralnet

neuralnet/NAMESPACE

neuralnet/R

neuralnet/R/compute.r

neuralnet/R/neuralnet.r

neuralnet/R/plot.nn.r

neuralnet/R/confidence.interval.r

neuralnet/R/prediction.r

neuralnet/R/gwplot.r

neuralnet/MD5

neuralnet/DESCRIPTION

neuralnet/man

neuralnet/man/neuralnet.Rd
neuralnet/man/prediction.Rd
neuralnet/man/compute.Rd
neuralnet/man/gwplot.Rd
neuralnet/man/neuralnet-package.Rd
neuralnet/man/plot.nn.Rd
neuralnet/man/confidence.interval.Rd
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