https://github.com/mlampros/elmnnrcpp

Extreme Learning Machine using RcppArmadillo
https://github.com/mlampros/elmnnrcpp

armadillo elm extreme-learning-machine r rcpparmadillo

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Extreme Learning Machine using RcppArmadillo

• Host: GitHub
• URL: https://github.com/mlampros/elmnnrcpp
• Owner: mlampros
• Created: 2018-07-05T18:43:01.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2023-05-27T04:40:09.000Z (over 1 year ago)
• Last Synced: 2024-04-25T22:02:12.715Z (8 months ago)
• Topics: armadillo, elm, extreme-learning-machine, r, rcpparmadillo
• Language: R
• Homepage: https://mlampros.github.io/elmNNRcpp/
• Size: 976 KB
• Stars: 15
• Watchers: 3
• Forks: 5
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        

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## elmNNRcpp ( Extreme Learning Machine )




The *elmNNRcpp* package is a reimplementation of *elmNN* using *RcppArmadillo* after the [*elmNN* package was archived](https://CRAN.R-project.org/package=elmNN). 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, Vignette and [blog-post](http://mlampros.github.io/2018/07/05/the_extreme_learning_machine_package/).





To install the package from CRAN use, 

```R

install.packages("elmNNRcpp")

```




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





```R

remotes::install_github('mlampros/elmNNRcpp')

```




Use the following link to report bugs/issues,





[https://github.com/mlampros/elmNNRcpp/issues](https://github.com/mlampros/elmNNRcpp/issues)




### **Citation:**

If you use the code of this repository in your paper or research please cite both **elmNNRcpp** and the **original articles / software** `https://CRAN.R-project.org/package=elmNNRcpp`:




```R

@Manual{,

  title = {{elmNNRcpp}: The Extreme Learning Machine Algorithm},

  author = {Lampros Mouselimis},

  year = {2022},

  note = {R package version 1.0.4},

  url = {https://CRAN.R-project.org/package=elmNNRcpp},

}

```