neuralnet: 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.

AuthorStefan Fritsch [aut], Frauke Guenther [aut, cre], Marc Suling [ctb], Sebastian M. Mueller [ctb]
Date of publication2016-08-16 12:08:44
MaintainerFrauke Guenther <guenther@leibniz-bips.de>
LicenseGPL (>= 2)
Version1.33

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Files

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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