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healthyR.ai: The Machine Learning and AI Modeling Companion to 'healthyR'

Hospital machine learning and ai data analysis workflow tools, modeling, and automations. This library provides many useful tools to review common administrative hospital data. Some of these include predicting length of stay, and readmits. The aim is to provide a simple and consistent verb framework that takes the guesswork out of everything.

Version: 0.1.0
Depends: R (≥ 3.3)
Imports: magrittr, rlang (≥ 0.1.2), yardstick (≥ 0.0.8), utils, broom, ggrepel, tibble, dplyr, ggplot2, tidyr, forcats, recipes (≥ 1.0.0), purrr, h2o, stats, dials, parsnip, tune, workflows, modeltime
Suggests: rmarkdown, knitr, healthyR.data, scales, tidyselect, janitor, timetk, plotly, rsample, kknn, hardhat, uwot, stringr
Published: 2024-09-11
DOI: 10.32614/CRAN.package.healthyR.ai
Author: Steven Sanderson ORCID iD [aut, cre, cph]
Maintainer: Steven Sanderson <spsanderson at gmail.com>
BugReports: https://github.com/spsanderson/healthyR.ai/issues
License: MIT + file LICENSE
URL: https://www.spsanderson.com/healthyR.ai/, https://github.com/spsanderson/healthyR.ai
NeedsCompilation: no
Materials: README NEWS
CRAN checks: healthyR.ai results

Documentation:

Reference manual: healthyR.ai.pdf
Vignettes: Auto K-Means with healthyR.ai (source, R code)
Getting Started with healthyR.ai (source, R code)
Clustering with K-Means and UMAP (source, R code)

Downloads:

Package source: healthyR.ai_0.1.0.tar.gz
Windows binaries: r-devel: healthyR.ai_0.1.0.zip, r-release: healthyR.ai_0.1.0.zip, r-oldrel: healthyR.ai_0.1.0.zip
macOS binaries: r-release (arm64): healthyR.ai_0.1.0.tgz, r-oldrel (arm64): healthyR.ai_0.0.13.tgz, r-release (x86_64): healthyR.ai_0.1.0.tgz, r-oldrel (x86_64): healthyR.ai_0.1.0.tgz
Old sources: healthyR.ai archive

Reverse dependencies:

Reverse imports: healthyverse
Reverse suggests: healthyR.ts

Linking:

Please use the canonical form https://CRAN.R-project.org/package=healthyR.ai 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.