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MNLR: Interactive Shiny Presentation for Working with MultinomialLogistic Regression

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

Documentation:

Reference manual:

MNLR.html ,MNLR.pdf

Downloads:

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

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=MNLRto link to this page.