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Streamlines the training, evaluation, and comparison of multiple machine learning models with minimal code by providing comprehensive data preprocessing and support for a wide range of algorithms with hyperparameter tuning. It offers performance metrics and visualization tools to facilitate efficient and effective machine learning workflows.
Version: | 0.1.0 |
Imports: | caret, pROC, reshape2, ggplot2, foreach, doParallel |
Suggests: | knitr, rmarkdown, randomForest, kernlab, gbm, nnet, rpart, glmnet, xgboost, pls, C50, mboost, arm, ipred, caTools, e1071, MASS |
Published: | 2024-11-12 |
DOI: | 10.32614/CRAN.package.fastml |
Author: | Selcuk Korkmaz [aut, cre], Dincer Goksuluk [aut] |
Maintainer: | Selcuk Korkmaz <selcukorkmaz at gmail.com> |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
NeedsCompilation: | no |
Materials: | README |
CRAN checks: | fastml results |
Reference manual: | fastml.pdf |
Package source: | fastml_0.1.0.tar.gz |
Windows binaries: | r-devel: fastml_0.1.0.zip, r-release: fastml_0.1.0.zip, r-oldrel: fastml_0.1.0.zip |
macOS binaries: | r-release (arm64): fastml_0.1.0.tgz, r-oldrel (arm64): fastml_0.1.0.tgz, r-release (x86_64): fastml_0.1.0.tgz, r-oldrel (x86_64): fastml_0.1.0.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.