Provides tools for general-purpose continuous optimization and feed-forward artificial neural network training using metaheuristic and gradient-based optimization algorithms. The package supports benchmark function optimization, regression, binary classification, and multi-class classification with multilayer perceptrons. The package implements several optimization methods, including particle swarm optimization Kennedy and Eberhart (1995) <doi:10.1109/ICNN.1995.488968>, differential evolution Storn and Price (1997) <doi:10.1023/A:1008202821328>, grey wolf optimizer Mirjalili et al. (2014) <doi:10.1016/j.advengsoft.2013.12.007>, secretary bird optimization Fu et al. (2024) <doi:10.1007/s10462-024-10729-y>, and Adam Kingma and Ba (2015) <doi:10.48550/arXiv.1412.6980>.
| Version: | 0.1.0 |
| Published: | 2026-05-15 |
| DOI: | 10.32614/CRAN.package.metANN |
| Author: | Burak Dilber [aut, cre, cph], A. Fırat Özdemir [aut, ths] |
| Maintainer: | Burak Dilber <burakdilber91 at gmail.com> |
| BugReports: | https://github.com/burakdilber/metANN/issues |
| License: | MIT + file LICENSE |
| URL: | https://github.com/burakdilber/metANN |
| NeedsCompilation: | no |
| Citation: | metANN citation info |
| Materials: | README |
| CRAN checks: | metANN results |
| Reference manual: | metANN.html , metANN.pdf |
| Package source: | metANN_0.1.0.tar.gz |
| Windows binaries: | r-devel: metANN_0.1.0.zip, r-release: metANN_0.1.0.zip, r-oldrel: metANN_0.1.0.zip |
| macOS binaries: | r-release (arm64): metANN_0.1.0.tgz, r-oldrel (arm64): metANN_0.1.0.tgz, r-release (x86_64): metANN_0.1.0.tgz, r-oldrel (x86_64): metANN_0.1.0.tgz |
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