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brnn  

Bayesian Regularization for Feed-Forward Neural Networks
View on CRAN: Click here


Download and install brnn package within the R console
Install from CRAN:
install.packages("brnn")

Install from Github:
library("remotes")
install_github("cran/brnn")

Install by package version:
library("remotes")
install_version("brnn", "0.9.3")



Attach the package and use:
library("brnn")
Maintained by
Paulino Perez Rodriguez
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2012-12-06
Latest Update: 2023-11-10
Description:
Bayesian regularization for feed-forward neural networks.
How to cite:
Paulino Perez Rodriguez (2012). brnn: Bayesian Regularization for Feed-Forward Neural Networks. R package version 0.9.3, https://cran.r-project.org/web/packages/brnn. Accessed 22 Dec. 2024.
Previous versions and publish date:
0.1 (2012-12-06 16:10), 0.3 (2013-03-15 13:28), 0.4 (2014-12-05 05:01), 0.5 (2015-01-08 20:03), 0.6 (2016-01-26 23:24), 0.7 (2018-08-23 15:54), 0.8 (2020-01-09 00:01), 0.9.1 (2022-04-25 18:30), 0.9.2 (2022-05-16 23:00), 0.9 (2021-09-09 20:40)
Other packages that cited brnn R package
View brnn citation profile
Other R packages that brnn depends, imports, suggests or enhances
Complete documentation for brnn
Functions, R codes and Examples using the brnn R package
Some associated functions: D . G . GOrd . brnn . brnn_extended . brnn_ordinal . estimate.trace . initnw . jacobian . normalize . partitions . pheno . phenoOrd . predictions.brnn . predictions.brnn_extended . predictions.brnn_ordinal . twoinput . un_normalize . 
Some associated R codes: brnn.R . methods.R .  Full brnn package functions and examples
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