# --------------------------------------------
# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "elmNNRcpp" in publications use:'
type: software
license: GPL-2.0-or-later
title: 'elmNNRcpp: The Extreme Learning Machine Algorithm'
version: 1.0.4
identifiers:
- type: doi
  value: 10.32614/CRAN.package.elmNNRcpp
abstract: '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, <https://doi.org/10.1016/j.neucom.2005.12.126>.'
authors:
- family-names: Mouselimis
  given-names: Lampros
  email: mouselimislampros@gmail.com
  orcid: https://orcid.org/0000-0002-8024-1546
- family-names: Gosso
  given-names: Alberto
  email: gosso.alberto@gmail.com
preferred-citation:
  type: manual
  title: 'elmNNRcpp: The Extreme Learning Machine Algorithm'
  authors:
  - family-names: Mouselimis
    given-names: Lampros
    email: mouselimislampros@gmail.com
    orcid: https://orcid.org/0000-0002-8024-1546
  year: '2022'
  notes: R package version 1.0.4
  url: https://CRAN.R-project.org/package=elmNNRcpp
repository: https://CRAN.R-project.org/package=elmNNRcpp
repository-code: https://github.com/mlampros/elmNNRcpp
url: https://github.com/mlampros/elmNNRcpp
date-released: '2022-01-27'
contact:
- family-names: Mouselimis
  given-names: Lampros
  email: mouselimislampros@gmail.com
  orcid: https://orcid.org/0000-0002-8024-1546
references:
- type: manual
  title: 'elmNN: Implementation of ELM (Extreme Learning Machine ) algorithm for SLFN
    ( Single Hidden Layer Feedforward Neural Networks )'
  authors:
  - family-names: Gosso
    given-names: Alberto
  year: '2012'
- type: article
  title: Extreme Learning Machine for Regression and Multiclass Classification
  authors:
  - family-names: Huang
    given-names: G.-B.
  - family-names: Zhou
    given-names: H.
  - family-names: Ding
    given-names: X.
  - family-names: Zhang
    given-names: R.
  journal: IEEE Transactions on Systems, Man, and Cybernetics
  year: '2011'
  volume: '42'
  doi: 10.1109/TSMCB.2011.2168604
  start: '513'
  end: '529'
- type: article
  title: 'Extreme learning machine: Theory and applications'
  authors:
  - family-names: Huang
    given-names: G.-B.
  - family-names: Zhu
    given-names: Q.-Y.
  - family-names: Siew
    given-names: C.-K.
  journal: Neurocomputing
  year: '2006'
  volume: '70'
  doi: 10.1016/j.neucom.2005.12.126
  start: '489'
  end: '501'