Package: elmNNRcpp 1.0.5

Lampros Mouselimis

elmNNRcpp: The Extreme Learning Machine Algorithm

Training and predict functions for Single Hidden-layer Feedforward Neural Networks (SLFN) using the Extreme Learning Machine (ELM) algorithm. The 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. This is a reimplementation of the 'elmNN' package using 'RcppArmadillo' after the 'elmNN' package was archived. For more information, see "Extreme learning machine: Theory and applications" by Guang-Bin Huang, Qin-Yu Zhu, Chee-Kheong Siew (2006), Elsevier B.V, <doi:10.1016/j.neucom.2005.12.126>.

Authors:Lampros Mouselimis [aut, cre], Alberto Gosso [aut], Edwin de Jonge [ctb]

elmNNRcpp_1.0.5.tar.gz
elmNNRcpp_1.0.5.tar.gz(r-4.7-arm64)elmNNRcpp_1.0.5.tar.gz(r-4.7-x86_64)elmNNRcpp_1.0.5.tar.gz(r-4.6-arm64)elmNNRcpp_1.0.5.tar.gz(r-4.6-x86_64)
elmNNRcpp_1.0.5.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
elmNNRcpp/json (API)
NEWS

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

Bug tracker:https://github.com/mlampros/elmnnrcpp/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

On CRAN:

Conda:

openblascppopenmp

4.80 score 5 packages 42 scripts 926 downloads 2 mentions 4 exports 3 dependencies

Last updated from:8cf850fc38. Checks:2 ERROR, 4 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64ERROR128
linux-devel-x86_64OK127
source / vignettesOK207
linux-release-arm64ERROR130
linux-release-x86_64OK160
wasm-releaseOK117

Exports:elmelm_predictelm_trainonehot_encode

Dependencies:KernelKnnRcppRcppArmadillo

Extreme Learning Machine

Rendered fromextreme_learning_machine.Rmdusingknitr::rmarkdownon Jun 12 2026.

Last update: 2018-07-21
Started: 2018-07-05