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 <http://wbbpredictions.com/wp-content/uploads/2018/12/Redditbot_Paper.pdf>. 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: 1.2.0
Imports: FNN, stringi, beepr, ggplot2, keras, dplyr, readr, parallel, textclean, tm, e1071, SnowballC, data.table, fastmatch, neuralnet
Published: 2019-10-31
Author: Travis Barton (2018)
Maintainer: Travis Barton <tbarton at csumb.edu>
License: GPL-2
NeedsCompilation: no
Materials: README
CRAN checks: LilRhino results

Documentation:

Reference manual: LilRhino.pdf

Downloads:

Package source: LilRhino_1.2.0.tar.gz
Windows binaries: r-devel: LilRhino_1.2.0.zip, r-release: LilRhino_1.2.0.zip, r-oldrel: LilRhino_1.2.0.zip
macOS binaries: r-release (arm64): LilRhino_1.2.0.tgz, r-release (x86_64): LilRhino_1.2.0.tgz, r-oldrel: LilRhino_1.2.0.tgz
Old sources: LilRhino archive

Linking:

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