Toolkit for statistical, machine learning, and targeted learning analyses. Functionality includes loading & auto-installing packages, standardizing datasets, creating missingness indicators, imputing missing values, creating multicore or multinode clusters, automatic SLURM integration, enhancing SuperLearner and TMLE with automatic parallelization, and many other SuperLearner analysis & plotting enhancements.
Version: | 1.0.3 |
Depends: | R (≥ 3.1.0) |
Imports: | caret, checkmate, crayon, cvAUC, doParallel, foreach, future.apply, ggplot2, h2o, methods, parallel, precrec, pryr, reader, RhpcBLASctl, ROCR, rpart.plot, stringr, SuperLearner, tmle, weights |
Suggests: | data.table, dplyr, glmnet, lintr, MASS, magrittr, mgcv, microbenchmark, mlbench, randomForest, RANN, slam, testthat, xgboost |
Published: | 2020-02-06 |
Author: | Chris Kennedy |
Maintainer: | Chris Kennedy <chrisken at gmail.com> |
BugReports: | https://github.com/ck37/ck37r/issues |
License: | MIT + file LICENSE |
URL: | https://github.com/ck37/ck37r |
NeedsCompilation: | no |
Materials: | NEWS |
CRAN checks: | ck37r results |
Reference manual: | ck37r.pdf |
Package source: | ck37r_1.0.3.tar.gz |
Windows binaries: | r-devel: ck37r_1.0.3.zip, r-devel-gcc8: not available, r-release: ck37r_1.0.3.zip, r-oldrel: ck37r_1.0.3.zip |
OS X binaries: | r-release: not available, r-oldrel: not available |
Old sources: | ck37r archive |
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