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LilRhino: For Implementation of Feed Reduction, Learning Examples, NLP and Code Management

This is for code management functions, NLP tools, a Monty Hall simulator, and for implementing my own variable reduction technique called Feed Reduction. The Feed Reduction technique is not yet published, but is merely a tool for implementing a series of binary neural networks meant for reducing data into N dimensions, where N is the number of possible values of the response variable.

Version: 1.2.2
Imports: FNN, stringi, beepr, ggplot2, keras, dplyr, readr, parallel, tm, e1071, SnowballC, data.table, fastmatch, neuralnet
Suggests: textclean
Published: 2022-04-27
DOI: 10.32614/CRAN.package.LilRhino
Author: Travis Barton (2018)
Maintainer: Travis Barton <travisdatabarton at gmail.com>
License: GPL-2
NeedsCompilation: no
Materials: README
CRAN checks: LilRhino results

Documentation:

Reference manual: LilRhino.pdf

Downloads:

Package source: LilRhino_1.2.2.tar.gz
Windows binaries: r-devel: LilRhino_1.2.2.zip, r-release: LilRhino_1.2.2.zip, r-oldrel: LilRhino_1.2.2.zip
macOS binaries: r-release (arm64): LilRhino_1.2.2.tgz, r-oldrel (arm64): LilRhino_1.2.2.tgz, r-release (x86_64): LilRhino_1.2.2.tgz, r-oldrel (x86_64): LilRhino_1.2.2.tgz
Old sources: LilRhino archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=LilRhino to link to this page.

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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