brnn v0.8
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Bayesian Regularization for Feed-Forward Neural Networks
Bayesian regularization for feed-forward neural networks.
Functions in brnn
Name | Description | |
estimate.trace | estimate.trace | |
GOrd | Genomic additive relationship matrix for the GLS dataset. | |
brnn_ordinal | brnn_ordinal | |
normalize | normalize | |
phenoOrd | Phenotypic information for GLS (ordinal trait) | |
predict.brnn_ordinal | predict.brnn_ordinal | |
predict.brnn_extended | predict.brnn_extended | |
twoinput | 2 Inputs and 1 output. | |
un_normalize | un_normalize | |
brnn | brnn | |
partitions | Partitions for cross validation (CV) | |
pheno | Phenotypic information for Jersey | |
predict.brnn | predict.brnn | |
G | Genomic additive relationship matrix for the Jersey dataset. | |
D | Genomic dominant relationship matrix for the Jersey dataset. | |
jacobian | Jacobian | |
brnn_extended | brnn_extended | |
initnw | Initialize networks weights and biases | |
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Details
Date | 2020-01-04 |
LazyLoad | true |
License | GPL-2 |
NeedsCompilation | yes |
Packaged | 2020-01-05 17:32:37 UTC; paulino |
Repository | CRAN |
Date/Publication | 2020-01-08 23:01:53 UTC |
depends | Formula , R (>= 3.5.0) , truncnorm |
Contributors | Paulino Rodriguez, Daniel Gianola |
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[](http://www.rdocumentation.org/packages/brnn)