Training of general classification and regression neural networks using gradient descent. Special features include a function for training replicator neural networks and a function for training autoencoders. Multiple activation and cost functions (including Huber and pseudo-Huber) are supported, as well as L1 and L2 regularization, momentum, early stopping and the possibility to specify a learning rate schedule. The package contains a vectorized gradient descent implementation which facilitates faster training through batch learning.
| Version: | 1.1 |
| Imports: | Rcpp (≥ 0.12.12), robustbase (≥ 0.92), stats (≥ 3.3.2), graphics (≥ 3.3.2) |
| LinkingTo: | Rcpp, RcppArmadillo |
| Suggests: | rgl, reshape2 |
| Published: | 2017-10-23 |
| Author: | Bart Lammers |
| Maintainer: | Bart Lammers <bart.f.lammers at gmail.com> |
| License: | GPL (≥ 3) |
| URL: | https://github.com/bflammers/ANN2 |
| NeedsCompilation: | yes |
| CRAN checks: | ANN2 results |
| Reference manual: | ANN2.pdf |
| Package source: | ANN2_1.1.tar.gz |
| Windows binaries: | r-devel: ANN2_1.0.zip, r-release: ANN2_1.0.zip, r-oldrel: ANN2_1.0.zip |
| OS X El Capitan binaries: | r-release: ANN2_1.0.tgz |
| OS X Mavericks binaries: | r-oldrel: ANN2_1.0.tgz |
| Old sources: | ANN2 archive |
Please use the canonical form https://CRAN.R-project.org/package=ANN2 to link to this page.