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An interactive presentation on the topic of Multinomial Logistic Regression. It is helpful to those who want to learn Multinomial Logistic Regression quickly and get a hands on experience. The presentation has a template for solving problems on Multinomial Logistic Regression. Runtime examples are provided in the package function as well as at <https://jarvisatharva.shinyapps.io/MultinomPresentation>.
| Version: | 0.1.0 |
| Depends: | R (≥ 3.0.3) |
| Imports: | shiny, rmarkdown, nnet, e1071, caret, datasets, stats |
| Published: | 2019-03-23 |
| DOI: | 10.32614/CRAN.package.MNLR |
| Author: | Kartikeya Bolar |
| Maintainer: | Kartikeya Bolar <kartikeya.bolar at tapmi.edu.in> |
| License: | GPL-2 |
| NeedsCompilation: | no |
| CRAN checks: | MNLR results |
| Reference manual: | MNLR.pdf |
| Package source: | MNLR_0.1.0.tar.gz |
| Windows binaries: | r-devel: MNLR_0.1.0.zip, r-release: MNLR_0.1.0.zip, r-oldrel: MNLR_0.1.0.zip |
| macOS binaries: | r-release (arm64): MNLR_0.1.0.tgz, r-oldrel (arm64): MNLR_0.1.0.tgz, r-release (x86_64): MNLR_0.1.0.tgz, r-oldrel (x86_64): MNLR_0.1.0.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.
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