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.
| Version: | 1.2.0 |
| Depends: | R (≥ 3.2.3) |
| Imports: | caret, data.table, DBI, doParallel, dplyr, e1071, grpreg, lme4, odbc, pROC, R6, ranger, ROCR, RSQLite, xgboost |
| Suggests: | testthat |
| Published: | 2017-10-27 |
| Author: | Levi Thatcher [aut], Michael Levy [aut, cre], Mike Mastanduno [aut], Taylor Larsen [aut], Taylor Miller [aut] |
| Maintainer: | Michael Levy <michael.levy at healthcatalyst.com> |
| BugReports: | https://github.com/HealthCatalyst/healthcareai-r/issues |
| License: | MIT + file LICENSE |
| URL: | http://healthcareai-r.readthedocs.io |
| NeedsCompilation: | no |
| Materials: | README |
| CRAN checks: | healthcareai results |
| Reference manual: | healthcareai.pdf |
| Package source: | healthcareai_1.2.0.tar.gz |
| Windows binaries: | r-devel: healthcareai_1.2.0.zip, r-release: healthcareai_1.2.0.zip, r-oldrel: healthcareai_1.2.0.zip |
| OS X El Capitan binaries: | r-release: healthcareai_1.2.0.tgz |
| OS X Mavericks binaries: | r-oldrel: healthcareai_1.2.0.tgz |
| Old sources: | healthcareai archive |
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