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>.

Package details

AuthorLampros Mouselimis [aut, cre] (<https://orcid.org/0000-0002-8024-1546>), Alberto Gosso [aut], Edwin de Jonge [ctb] (<https://orcid.org/0000-0002-6580-4718>, Github Contributor)
MaintainerLampros Mouselimis <mouselimislampros@gmail.com>
LicenseGPL (>= 2)
Version1.0.4
URL https://github.com/mlampros/elmNNRcpp
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("elmNNRcpp")

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elmNNRcpp documentation built on March 18, 2022, 7:26 p.m.