neuralnet v1.44.2
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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.
Functions in neuralnet
Name | Description | |
compute | Deprecated function | |
neuralnet | Training of neural networks | |
plot.nn | Plot method for neural networks | |
gwplot | Plot method for generalized weights | |
neuralnet-package | Training of Neural Networks | |
predict.nn | Neural network prediction | |
prediction | Summarizes the output of the neural network, the data and the fitted values of glm objects (if available) | |
confidence.interval | Calculates confidence intervals of the weights | |
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Details
Type | Package |
Date | 2019-02-07 |
License | GPL (>= 2) |
URL | https://github.com/bips-hb/neuralnet |
BugReports | https://github.com/bips-hb/neuralnet/issues |
RoxygenNote | 6.1.0 |
NeedsCompilation | no |
Packaged | 2019-02-07 21:47:31 UTC; wright |
Repository | CRAN |
Date/Publication | 2019-02-07 22:20:07 UTC |
imports | Deriv , grDevices , grid , MASS , stats , utils |
depends | R (>= 2.9.0) |
suggests | testthat |
Contributors | Stefan Fritsch, Marc Suling, Frauke Guenther, Sebastian M. Mueller |
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