Tools for Healthcare Machine Learning

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, Extreme Gradient Boosting, K-means clustering, and Linear Mixed Modeling.


Reference manual

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1.2.0 by Michael Levy, a month ago

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Authors: Levi Thatcher [aut], Michael Levy [aut, cre], Mike Mastanduno [aut], Taylor Larsen [aut], Taylor Miller [aut]

Documentation:   PDF Manual  

MIT + file LICENSE license

Imports caret, data.table, DBI, doParallel, dplyr, e1071, grpreg, lme4, odbc, pROC, R6, ranger, ROCR, RSQLite, xgboost

Suggests testthat

See at CRAN