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elmNNRcpp  

The Extreme Learning Machine Algorithm
View on CRAN: Click here


Download and install elmNNRcpp package within the R console
Install from CRAN:
install.packages("elmNNRcpp")

Install from Github:
library("remotes")
install_github("cran/elmNNRcpp")

Install by package version:
library("remotes")
install_version("elmNNRcpp", "1.0.4")



Attach the package and use:
library("elmNNRcpp")
Maintained by
Lampros Mouselimis
[Scholar Profile | Author Map]
First Published: 2018-07-05
Latest Update: 2022-01-28
Description:
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, .
How to cite:
Lampros Mouselimis (2018). elmNNRcpp: The Extreme Learning Machine Algorithm. R package version 1.0.4, https://cran.r-project.org/web/packages/elmNNRcpp. Accessed 06 Apr. 2025.
Previous versions and publish date:
1.0.0 (2018-07-05 10:30), 1.0.1 (2018-07-21 22:00), 1.0.2 (2020-06-13 14:40), 1.0.3 (2021-05-04 07:30)
Other packages that cited elmNNRcpp R package
View elmNNRcpp citation profile
Other R packages that elmNNRcpp depends, imports, suggests or enhances
Complete documentation for elmNNRcpp
Functions, R codes and Examples using the elmNNRcpp R package
Some associated functions: elm . elm_predict . elm_train . onehot_encode . predict.elm . 
Some associated R codes: RcppExports.R . elm.R . elmNNRcpp.R . utils.R .  Full elmNNRcpp package functions and examples
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