Package: brnn 0.9.3

Paulino Perez Rodriguez

brnn: Bayesian Regularization for Feed-Forward Neural Networks

Bayesian regularization for feed-forward neural networks.

Authors:Paulino Perez Rodriguez, Daniel Gianola

brnn_0.9.3.tar.gz
brnn_0.9.3.tar.gz(r-4.5-noble)brnn_0.9.3.tar.gz(r-4.4-noble)
brnn_0.9.3.tgz(r-4.4-emscripten)brnn_0.9.3.tgz(r-4.3-emscripten)
brnn.pdf |brnn.html
brnn/json (API)

# Install 'brnn' in R:
install.packages('brnn', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • openblas– Optimized BLAS
  • openmp– GCC OpenMP (GOMP) support library
Datasets:
  • D - Genomic dominant relationship matrix for the Jersey dataset.
  • G - Genomic additive relationship matrix for the Jersey dataset.
  • GOrd - Genomic additive relationship matrix for the GLS dataset.
  • partitions - Partitions for cross validation
  • pheno - Phenotypic information for Jersey
  • phenoOrd - Phenotypic information for GLS
  • twoinput - 2 Inputs and 1 output.

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

openblasopenmp

3.89 score 5 packages 106 scripts 1.6k downloads 3 mentions 18 exports 2 dependencies

Last updated 1 years agofrom:2ebade193b. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKDec 04 2024
R-4.5-linux-x86_64OKDec 04 2024

Exports:brnnbrnn_extendedbrnn_ordinalcoef.brnncoef.brnn_extendedestimate.traceinitnwnormalizepredict.brnnpredict.brnn_extendedpredict.brnn_ordinalprint.brnnprint.brnn_extendedprint.brnn_ordinalsummary.brnnsummary.brnn_extendedsummary.brnn_ordinalun_normalize

Dependencies:Formulatruncnorm

Readme and manuals

Help Manual

Help pageTopics
brnnbrnn brnn.default brnn.formula coef.brnn print.brnn summary.brnn
brnn_extendedbrnn_extended brnn_extended.default brnn_extended.formula coef.brnn_extended print.brnn_extended summary.brnn_extended
brnn_ordinalbrnn_ordinal brnn_ordinal.default brnn_ordinal.formula print.brnn_ordinal summary.brnn_ordinal
Genomic dominant relationship matrix for the Jersey dataset.D
estimate.traceestimate.trace
Genomic additive relationship matrix for the Jersey dataset.G
Genomic additive relationship matrix for the GLS dataset.GOrd
Initialize networks weights and biasesinitnw
Jacobianjacobian
normalizenormalize
Partitions for cross validation (CV)partitions
Phenotypic information for Jerseypheno
Phenotypic information for GLS (ordinal trait)phenoOrd
predict.brnnpredict.brnn
predict.brnn_extendedpredict.brnn_extended
predict.brnn_ordinalpredict.brnn_ordinal
2 Inputs and 1 output.twoinput
un_normalizeun_normalize