distributions, or multivariate truncated normal (MTN). Techniques include
zigzag Hamiltonian Monte  Carlo as in Akihiko Nishimura, Zhenyu Zhang and
Marc A. Suchard (2021) <arXiv:2104.07694>, and  harmonic Monte in Ari Pakman
Packaged: 2022-08-06 22:05:39 UTC; zhenyuzhang

Title: Compose Sentences to Describe Comparisons
Description: Create dynamic, data-driven text. Given two values, a list of
talking points is generated and can be combined using string
interpolation. Based on the 'glue' package.
Suggests: ggplot2, knitr, nycflights13, rmarkdown, testthat
Imports: dplyr, glue, lubridate, purrr, rlang, tibble, tidyr

Title: Tools for Healthcare Machine Learning
person("Levi", "Thatcher", email = "levi.thatcher@healthcatalyst.com", role = c("aut", "cre")),
person("Mike", "Mastanduno", email = "mike.mastanduno@healthcatalyst.com", role = "aut"),
person("Taylor", "Miller", email = "taylor.miller@healthcatalyst.com", role = "aut"),
person("Taylor", "Larsen", email = "taylor.larsen@healthcatalyst.com", role = "aut"))
Description: A machine learning toolbox tailored to healthcare data.
Aids in data cleaning, model development, hyperparameter tuning, and model
deployment in a production SQL environment. Algorithms currently supported
are Lasso, Random Forest, and Linear Mixed Model.
Imports: caret, data.table, doParallel, e1071, grpreg, lme4, lubridate,
Packaged: 2017-02-10 03:28:44 UTC; michael.mastanduno

Imports: caret, data.table, DBI, doParallel, e1071, grpreg, lme4, odbc,
Packaged: 2017-05-04 22:37:11 UTC; michael.mastanduno

person("Mike", "Mastanduno", email = "michael.mastanduno@healthcatalyst.com", role = "aut"),
person("Michael", "Levy", email = "michael.levy@healthcatalyst.com", role = "aut"),
are Lasso, Random Forest, XGBoost, Kmeans clustering, and Linear Mixed Model.
pROC, R6, ranger, ROCR, RSQLite, xgboost
Packaged: 2017-09-11 16:21:45 UTC; michael.mastanduno

person("Levi", "Thatcher", email = "levi.thatcher@healthcatalyst.com", role = "aut"),
person("Michael", "Levy", email = "michael.levy@healthcatalyst.com", role = c("aut", "cre")),
person("Taylor", "Larsen", email = "taylor.larsen@healthcatalyst.com", role = "aut"),
person("Taylor", "Miller", email = "taylor.miller@healthcatalyst.com", role = "aut"))
deployment in a production 'SQL' environment. Algorithms currently supported
are Lasso, Random Forest, Extreme Gradient Boosting, K-means clustering, and Linear Mixed Modeling.
Imports: caret, data.table, DBI, doParallel, dplyr, e1071, grpreg,
lme4, odbc, pROC, R6, ranger, ROCR, RSQLite, xgboost
Packaged: 2017-10-25 22:31:59 UTC; michael.levy