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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 |
| Reference manual: | RWNN.pdf |
| 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 |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.