brnn: Bayesian Regularization for Feed-Forward Neural Networks
Version 0.6

Bayesian regularization for feed-forward neural networks.

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AuthorPaulino Perez Rodriguez, Daniel Gianola
Date of publication2016-01-26 23:24:30
MaintainerPaulino Perez Rodriguez <perpdgo@colpos.mx>
LicenseGPL-2
Version0.6
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("brnn")

Man pages

brnn: brnn
brnn_extended: brnn_extended
D: Genomic dominant relationship matrix for the Jersey dataset.
estimate.trace: estimate.trace
G: Genomic additive relationship matrix for the Jersey dataset.
initnw: Initialize networks weights and biases
jacobian: Jacobian
normalize: normalize
partitions: Partitions for cross validation (CV)
pheno: Phenotypic information for Jersey
predictions.brnn: predict.brnn
predictions.brnn_extended: predict.brnn_extended
twoinput: 2 Inputs and 1 output.
un_normalize: un_normalize

Functions

D Man page
Ew Source code
G Man page
brnn Man page Source code
brnn.default Man page Source code
brnn.formula Man page Source code
brnn_extended Man page Source code
brnn_extended.default Man page Source code
brnn_extended.formula Man page Source code
coef.brnn Man page Source code
coef.brnn_extended Man page Source code
estimate.trace Man page Source code
ii Source code
initnw Man page Source code
jacobian Man page Source code
normalize Man page Source code
onAttach Source code
partitions Man page
pheno Man page
predict.brnn Man page Source code
predict.brnn_extended Man page Source code
predictions.nn.C Source code
print.brnn Man page Source code
print.brnn_extended Man page Source code
sech Source code
summary.brnn Man page Source code
summary.brnn_extended Man page Source code
tanh Source code
tansig Source code
twoinput Man page
un_normalize Man page Source code

Files

COPYING
inst
inst/history.txt
src
src/Makevars
src/util.c
src/win
src/win/util_win.c
src/Lanczos.c
src/util.h
src/unix
src/unix/util_unix.c
src/Makevars.win
src/Lanczos.h
NAMESPACE
demo
demo/Example_3.R
demo/Example_1.R
demo/Example_5.R
demo/Example_4.R
demo/00Index
demo/Example_2.R
data
data/twoinput.RData
data/Jersey.RData
R
R/brnn.R
R/methods.R
MD5
DESCRIPTION
man
man/un_normalize.Rd
man/pheno.Rd
man/initnw.Rd
man/predictions.brnn.Rd
man/G.Rd
man/jacobian.Rd
man/brnn.Rd
man/D.Rd
man/estimate.trace.Rd
man/twoinput.Rd
man/brnn_extended.Rd
man/normalize.Rd
man/predictions.brnn_extended.Rd
man/partitions.Rd
brnn documentation built on May 19, 2017, 1:17 p.m.