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mlr : Machine Learning in R

Package: mlr
Title: Machine Learning in R
Description: Interface to a large number of classification and regression
techniques, including machine-readable parameter descriptions. There is
also an experimental extension for survival analysis, clustering and
general, example-specific cost-sensitive learning. Generic resampling,
including cross-validation, bootstrapping and subsampling. Hyperparameter
tuning with modern optimization techniques, for single- and multi-objective
problems. Filter and wrapper methods for feature selection. Extension of
basic learners with additional operations common in machine learning, also
allowing for easy nested resampling. Most operations can be parallelized.
Authors@R: c(person("Bernd", "Bischl", email = "bernd_bischl@gmx.net", role =
c("aut", "cre")), person("Michel", "Lang", email =
"michellang@gmail.com", role = "aut"), person("Jakob", "Richter", email =
"code@jakob-r.de", role = "aut"), person("Jakob", "Bossek",
email = "jakob.bossek@tu-dortmund.de", role = "aut"), person("Leonard",
"Judt", email = "leonard.judt@tu-dortmund.de", role = "aut"),
person("Tobias", "Kuehn", email = "tobi.kuehn@gmx.de", role = "aut"),
person("Erich", "Studerus", email = "erich.studerus@upkbs.ch", role =
"aut"), person("Lars", "Kotthoff", email =
"larsko@cs.ubc.ca", role = "aut"), person("Zachary", "Jones", email =
"zmj@zmjones.com", role = "ctb"), person("Schiffner", "Julia", email =
"schiffner@math.uni-duesseldorf.de", role = "aut"))
URL: https://github.com/mlr-org/mlr
BugReports: https://github.com/mlr-org/mlr/issues
License: BSD_2_clause + file LICENSE
Encoding: UTF-8
Depends: R (>= 3.0.2), BBmisc (>= 1.9), ggplot2, ParamHelpers (>= 1.7),
stats
Imports: checkmate (>= 1.7.1), ggvis, methods, parallelMap (>= 1.3),
plyr, reshape2, shiny, survival
Suggests: ada, adabag, bartMachine, brnn, bst, care, caret (>= 6.0-57),
class, clue, cluster, clusterSim, clValid, cmaes, CoxBoost,
crs, Cubist, deepnet, DiceKriging, DiceOptim, DiscriMiner,
e1071, earth, elasticnet, elmNN, emoa, extraTrees, flare,
fields, FNN, fpc, frbs, FSelector, gbm, GenSA, glmnet, Hmisc,
irace (>= 1.0.7), kernlab, kknn, klaR, knitr, kohonen, laGP,
LiblineaR, lqa, MASS, mboost, mco, mda, mlbench, modeltools,
mRMRe, nnet, nodeHarvest (>= 0.7-3), neuralnet, numDeriv, pamr,
party, penalized, pls, PMCMR, pROC (>= 1.8), randomForest,
randomForestSRC (>= 2.0.5), ranger (>= 0.3.0), RCurl, rFerns,
rjson, rknn, rmarkdown, robustbase, ROCR, rotationForest,
rpart, rrlda, rsm, RSNNS, RWeka, sda, sparsediscrim, sparseLDA,
stepPlr, SwarmSVM, testthat, tgp, TH.data, xgboost, XML
LazyData: yes
ByteCompile: yes
Version: 2.8
VignetteBuilder: knitr
RoxygenNote: 5.0.1
NeedsCompilation: yes
Packaged: 2016-02-12 14:47:04 UTC; bischl
Author: Bernd Bischl [aut, cre],
Michel Lang [aut],
Jakob Richter [aut],
Jakob Bossek [aut],
Leonard Judt [aut],
Tobias Kuehn [aut],
Erich Studerus [aut],
Lars Kotthoff [aut],
Zachary Jones [ctb],
Schiffner Julia [aut]
Maintainer: Bernd Bischl <bernd_bischl@gmx.net>
Repository: CRAN
Date/Publication: 2016-02-13 08:37:35

● Data Source: CranContrib
● Cran Task View: MachineLearning
● 0 images, 185 functions, 2 datasets
Reverse Depends: 3