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, .



The elmNNRcpp package is a reimplementation of elmNN using RcppArmadillo after the elmNN package was archived. Based on the documentation of the elmNN it consists of, "Training and predict functions for SLFN ( Single Hidden-layer Feedforward Neural Networks ) using the 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.". More details can be found in the package Documentation and Vignette.

To install the package from CRAN use,

 
install.packages("elmNNRcpp")
 
 

and to download the latest version from Github use the install_github function of the devtools package,

 
devtools::install_github('mlampros/elmNNRcpp')
 
 

Use the following link to report bugs/issues,

https://github.com/mlampros/elmNNRcpp/issues

News

elmNNRcpp 1.0.1

I added the Github repository Url and the BugReports Url in the DESCRIPTION file.

elmNNRcpp 1.0.0

Reference manual

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install.packages("elmNNRcpp")

1.0.1 by Lampros Mouselimis, 8 months ago


https://github.com/mlampros/elmNNRcpp


Report a bug at https://github.com/mlampros/elmNNRcpp/issues


Browse source code at https://github.com/cran/elmNNRcpp


Authors: Lampros Mouselimis [aut, cre] , Alberto Gosso [aut]


Documentation:   PDF Manual  


GPL (>= 2) license


Imports Rcpp

Depends on KernelKnn

Suggests testthat, covr, knitr, rmarkdown

Linking to Rcpp, RcppArmadillo


See at CRAN