mlr: mlr: Machine Learning in R

Interface to a large number of classification and regression techniques, including machine-readable parameter descriptions. Generic resampling, including cross-validation, bootstrapping and subsampling. Hyperparameter tuning with modern optimization techniques. Filter and wrapper methods for feature selection. Extension of basic learners with additional operations. Nested resampling.

Version: 1.1-18
Depends: R (≥ 3.0.0), ParamHelpers (≥ 1.1-36)
Imports: BBmisc (≥ 1.3-64), parallelMap, codetools
Suggests: testthat, snowfall, ada, adabag, cmaes, DiceKriging, DiceOptim, e1071, earth, FNN, FSelector, gbm, irace, kernlab, kknn, klaR, mboost, mda, mlbench, nnet, party, penalized, pls, randomForest, reshape, robustbase, rpart, rsm, RWeka, ROCR
Published: 2013-08-30
Author: Bernd Bischl
Maintainer: Bernd Bischl <bernd_bischl at gmx.net>
BugReports: https://github.com/berndbischl/mlr/issues
License: BSD_3_clause + file LICENSE
URL: https://github.com/berndbischl/mlr
NeedsCompilation: no
CRAN checks: mlr results

Downloads:

Reference manual: mlr.pdf
Package source: mlr_1.1-18.tar.gz
OS X binary: mlr_1.1-18.tgz
Windows binary: mlr_1.1-18.zip