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>
License: GPL-2
NeedsCompilation: no
Materials: README
CRAN checks: LilRhino results


Reference manual: LilRhino.pdf


Package source: LilRhino_1.2.2.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
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


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