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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 [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 |
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) |
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 imports: | healthyverse |
Reverse suggests: | healthyR.ts |
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.