RWNN: Random Weight Neural Networks

Creation, estimation, and prediction of random weight neural networks (RWNN), Schmidt et al. (1992) <doi:10.1109/ICPR.1992.201708>, including popular variants like extreme learning machines, Huang et al. (2006) <doi:10.1016/j.neucom.2005.12.126>, sparse RWNN, Zhang et al. (2019) <doi:10.1016/j.neunet.2019.01.007>, and deep RWNN, Henríquez et al. (2018) <doi:10.1109/IJCNN.2018.8489703>. It further allows for the creation of ensemble RWNNs like bagging RWNN, Sui et al. (2021) <doi:10.1109/ECCE47101.2021.9595113>, boosting RWNN, stacking RWNN, and ensemble deep RWNN, Shi et al. (2021) <doi:10.1016/j.patcog.2021.107978>.

Version: 0.4
Depends: R (≥ 4.1.0)
Imports: methods, quadprog, randtoolbox, Rcpp (≥ 1.0.4.6), stats, utils
LinkingTo: Rcpp, RcppArmadillo
Suggests: tinytest
Published: 2024-09-03
DOI: 10.32614/CRAN.package.RWNN
Author: Søren B. Vilsen [aut, cre]
Maintainer: Søren B. Vilsen <svilsen at math.aau.dk>
License: MIT + file LICENSE
NeedsCompilation: yes
CRAN checks: RWNN results

Documentation:

Reference manual: RWNN.pdf

Downloads:

Package source: RWNN_0.4.tar.gz
Windows binaries: r-devel: RWNN_0.4.zip, r-release: RWNN_0.4.zip, r-oldrel: RWNN_0.4.zip
macOS binaries: r-release (arm64): RWNN_0.4.tgz, r-oldrel (arm64): RWNN_0.4.tgz, r-release (x86_64): RWNN_0.4.tgz, r-oldrel (x86_64): RWNN_0.4.tgz

Linking:

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