There are different numeric optimizations which are used in order to estimate coefficients in models such as linear regression and neural networks. This package covers parameter estimation in linear regression using different methods such as batch gradient descent, stochastic gradient descent, minibatch gradient descent and coordinate descent. Kiwiel, Krzysztof C (2001) <doi:10.1007/PL00011414> Yu Nesterov (2004) <ISBN:1-4020-7553-7> Ferguson, Thomas S (1982) <doi:10.1080/01621459.1982.10477894> Zeiler, Matthew D (2012) <arXiv:1212.5701> Wright, Stephen J (2015) <arXiv:1502.04759>.
| Version: | 1.0 |
| Suggests: | testthat, knitr, rmarkdown, stats |
| Published: | 2018-06-04 |
| Author: | Akshay Suresh, Siddhesh Acharekar, Hsiangwei Chao, Shiva Yogi Biradar |
| Maintainer: | Akshay Suresh <suresh.aks at husky.neu.edu> |
| License: | MIT + file LICENSE |
| NeedsCompilation: | no |
| CRAN checks: | rcane results |
| Reference manual: | rcane.pdf |
| Vignettes: |
Vignette Title |
| Package source: | rcane_1.0.tar.gz |
| Windows binaries: | r-devel: rcane_1.0.zip, r-release: rcane_1.0.zip, r-oldrel: rcane_1.0.zip |
| macOS binaries: | r-release: rcane_1.0.tgz, r-oldrel: rcane_1.0.tgz |
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