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healthyR.ai
View on CRAN: Click
here
Download and install healthyR.ai package within the R console
Install from CRAN:
install.packages("healthyR.ai")
Install from Github:
library("remotes")
install_github("cran/healthyR.ai") Install by package version:
library("remotes")
install_version("healthyR.ai", "0.1.1") Attach the package and use:
library("healthyR.ai")
Maintained by
Steven Sanderson
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-08-20
Latest Update: 2025-04-24
Description:
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.
How to cite:
Steven Sanderson (2021). healthyR.ai: The Machine Learning and AI Modeling Companion to 'healthyR'. R package version 0.1.1, https://cran.r-project.org/web/packages/healthyR.ai. Accessed 14 Sep. 2026.
Previous versions and publish date:
(2026-08-21 16:41), 0.0.1 (2021-08-20 14:30), 0.0.2 (2021-09-03 02:10), 0.0.3 (2021-11-23 16:10), 0.0.4 (2021-12-08 22:30), 0.0.5 (2022-01-07 14:32), 0.0.6 (2022-02-28 00:20), 0.0.7 (2022-04-29 21:20), 0.0.8 (2022-07-04 15:30), 0.0.9 (2022-10-04 16:30), 0.0.10 (2022-11-16 13:10), 0.0.11 (2023-01-12 18:20), 0.0.12 (2023-02-01 19:40), 0.0.13 (2023-04-03 02:20), 0.1.0 (2024-09-11 08:50), 0.1.1 (2025-04-24 13:40)
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Other R packages that healthyR.ai depends,
imports, suggests or enhances
Complete documentation for healthyR.ai
Functions, R codes and Examples using
the healthyR.ai R package
Some associated functions: color_blind . get_juiced_data . hai_auto_c50 . hai_auto_cubist . hai_auto_earth . hai_auto_glmnet . hai_auto_knn . hai_auto_ranger . hai_auto_svm_poly . hai_auto_svm_rbf . hai_auto_wflw_metrics . hai_auto_xgboost . hai_c50_data_prepper . hai_control_chart . hai_cubist_data_prepper . hai_data_impute . hai_data_poly . hai_data_scale . hai_data_transform . hai_data_trig . hai_default_classification_metric_set . hai_default_regression_metric_set . hai_density_hist_plot . hai_density_plot . hai_density_qq_plot . hai_distribution_comparison_tbl . hai_earth_data_prepper . hai_fourier_augment . hai_fourier_discrete_augment . hai_fourier_discrete_vec . hai_fourier_vec . hai_get_density_data_tbl . hai_get_dist_data_tbl . hai_glmnet_data_prepper . hai_histogram_facet_plot . hai_hyperbolic_augment . hai_hyperbolic_vec . hai_kmeans_automl . hai_kmeans_automl_predict . hai_kmeans_mapped_tbl . hai_kmeans_obj . hai_kmeans_scree_data_tbl . hai_kmeans_scree_plt . hai_kmeans_tidy_tbl . hai_kmeans_user_item_tbl . hai_knn_data_prepper . hai_kurtosis_vec . hai_polynomial_augment . hai_range_statistic . hai_ranger_data_prepper . hai_scale_color_colorblind . hai_scale_fill_colorblind . hai_scale_zero_one_augment . hai_scale_zero_one_vec . hai_scale_zscore_augment . hai_scale_zscore_vec . hai_skewed_features . hai_skewness_vec . hai_svm_poly_data_prepper . hai_svm_rbf_data_prepper . hai_umap_list . hai_umap_plot . hai_winsorized_move_augment . hai_winsorized_move_vec . hai_winsorized_truncate_augment . hai_winsorized_truncate_vec . hai_xgboost_data_prepper . pca_your_recipe . pipe . required_pkgs.healthyR.ai . step_hai_fourier . step_hai_fourier_discrete . step_hai_hyperbolic . step_hai_scale_zero_one . step_hai_scale_zscore . step_hai_winsorized_move . step_hai_winsorized_truncate . tidyeval .
Some associated R codes: 00_global_variables.R . augment-hai-fourier-discrete.R . augment-hai-fourier.R . augment-hai-hyperbolic.R . augment-hai-polynomial.R . augment-hai-scale-zero-one.R . augment-hai-scale-zscore.R . augment-hai-windorized-move.R . augment-hai-winsorized-truncate.R . auto-kmeans-predict.R . auto-kmeans.R . boilerplate-c50.R . boilerplate-cubist.R . boilerplate-earth.R . boilerplate-glmnet.R . boilerplate-knn.R . boilerplate-metrics-collection.R . boilerplate-rangers.R . boilerplate-svm_poly.R . boilerplate-svm_rbf.R . boilerplate-xgboost.R . control-chart.R . data-prep-c50.R . data-prep-cubist.R . data-prep-earth.R . data-prep-glmnet.R . data-prep-knn.R . data-prep-ranger.R . data-prep-svm_poly.R . data-prep-svm_rbf.R . data-prep-xgboost.R . get-juiced-data.R . hai-data-impute-missing.R . hai-data-poly.R . hai-data-scale.R . hai-data-transform.R . hai-data-trig.R . hai-range-statistic.R . hai-skewed-features.R . kmean-funcs.R . metric-sets.R . pallette-color-blind.R . pca-data.R . plot-hai-density-histogram.R . plot-hai-density-qq.R . plot-hai-density.R . plot-hai-histogram-facet.R . step-hai-fourier-discrete.R . step-hai-fourier.R . step-hai-hyperbolic.R . step-hai-scale-zero-one.R . step-hai-scale-zscore.R . step-hai-winsorized-move.R . step-hai-winsorized-truncate.R . tbl-hai-distribution-comparison.R . tbl-hai-get-density-data.R . tbl-hai-get-dist-data.R . umap-list.R . umap-plot.R . utils-pipe.R . utils-tidy-eval.R . vec-hai-fourier-discrete.R . vec-hai-fourier.R . vec-hai-hyperbolic.R . vec-hai-kurtosis.R . vec-hai-scale-zero-one.R . vec-hai-scale-zscore.R . vec-hai-skewness.R . vec-hai-winsorized-move.R . vec-hai-winsorized-truncate.R . zzz.R . Full healthyR.ai package functions and examples
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