Package: mlr
Title: mlr: Machine Learning in R.
Description: Interface to a large number of classification and regression
    techniques, including machine-readable parameter descriptions. There is
    also a n experimental extension for surival analysis and cost-sensitive
    learning. 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 common in machine learning.
Author: Bernd Bischl <bernd_bischl@gmx.net>,
    Michel Lang <lang@statistik.tu-dortmund.de>,
    Jakob Richter <code@jakob-r.de>,
    Leonard Judt <leonard.judt@tu-dortmund.de>
Maintainer: Bernd Bischl <bernd_bischl@gmx.net>
URL: https://github.com/berndbischl/mlr
BugReports: https://github.com/berndbischl/mlr/issues
License: BSD_3_clause + file LICENSE
Depends: R (>= 3.0.0), ParamHelpers (>= 1.2), BBmisc (>= 1.7), stats
Imports: parallelMap (>= 1.1), codetools, survival, checkmate (>= 1.1)
Suggests: testthat, ada, adabag, class, cluster, cmaes, CoxBoost, crs,
        DiceKriging, DiceOptim, DiscriMiner, e1071, earth, FNN,
        FSelector, gbm, GenSA, ggplot2, glmnet, Hmisc, irace, kernlab,
        kknn, klaR, LiblineaR, mboost, mda, mlbench, mRMRe, nnet,
        party, penalized, pls, pROC, randomForest, randomForestSRC,
        reshape2, rrlda, robustbase, rpart, rsm, RWeka, ROCR, stepPlr
LazyData: yes
ByteCompile: yes
Version: 2.0
Packaged: 2014-07-03 21:45:30 UTC; bischl
NeedsCompilation: yes
Repository: CRAN
Date/Publication: 2014-07-04 02:25:14
