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 |
| Reference manual: | LilRhino.pdf |
| 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: LilRhino_1.2.0.tgz, r-oldrel: LilRhino_1.2.0.tgz |
| Old sources: | LilRhino archive |
Please use the canonical form https://CRAN.R-project.org/package=LilRhino to link to this page.