elmNN: Implementation of ELM (Extreme Learning Machine ) algorithm for SLFN ( Single Hidden Layer Feedforward Neural Networks )

Training and predict functions for SLFN ( Single Hidden-layer Feedforward Neural Networks ) using the ELM algorithm. ELM algorithm differs from the traditional gradient-based algorithms for very short training times ( it doesn't need any iterative tuning, this makes learning time very fast ) and there is no need to set any other parameters like learning rate, momentum, epochs, etc.

Version: 1.0
Depends: MASS
Published: 2012-07-18
Author: Alberto Gosso
Maintainer: Alberto Gosso <gosso.alberto at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: elmNN results


Reference manual: elmNN.pdf
Package source: elmNN_1.0.tar.gz
Windows binaries: r-devel: elmNN_1.0.zip, r-release: elmNN_1.0.zip, r-oldrel: elmNN_1.0.zip
OS X Snow Leopard binaries: r-release: elmNN_1.0.tgz, r-oldrel: elmNN_1.0.tgz
OS X Mavericks binaries: r-release: elmNN_1.0.tgz

Reverse dependencies:

Reverse suggests: mlr