R Graphical Manual

Last data update: 2014.03.03

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Results 1 - 7 of 7 found.
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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

netgen : Network Generator for Combinatorial Graph Problems

Package: netgen
Type: Package
Title: Network Generator for Combinatorial Graph Problems
Description: Methods for the generation of a wide range of network geographies,
e.g., grid networks or clustered networks. Useful for the generation of
benchmarking instances for the investigation of, e.g., Vehicle-Routing-Problems
or Travelling Salesperson Problems.
Version: 1.3
Date: 2016-01-21
Authors@R: c(person("Jakob", "Bossek", email = "j.bossek@gmail.com", role =
c("aut", "cre")))
Maintainer: Jakob Bossek <j.bossek@gmail.com>
URL: https://github.com/jakobbossek/netgen
BugReports: https://github.com/jakobbossek/netgen/issues
License: BSD_3_clause + file LICENSE
Depends: BBmisc (>= 1.6), mvtnorm (>= 1.0-2), lhs (>= 0.10), checkmate
(>= 1.5.1)
Imports: ggplot2, lpSolve, igraph (>= 0.7.1), stringr (>= 0.6.2)
Suggests: testthat
LazyData: yes
ByteCompile: yes
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2016-01-21 23:04:49 UTC; jboss
Author: Jakob Bossek [aut, cre]
Repository: CRAN
Date/Publication: 2016-01-22 10:26:50

● Data Source: CranContrib
● 0 images, 30 functions, 0 datasets
● Reverse Depends: 0

cmaesr : Covariance Matrix Adaptation Evolution Strategy

Package: cmaesr
Type: Package
Title: Covariance Matrix Adaptation Evolution Strategy
Description: Pure R implementation of the Covariance Matrix Adaptation -
Evolution Strategy (CMA-ES) with optional restarts (IPOP-CMA-ES).
Version: 1.0.1
Date: 2016-01-18
Authors@R: c(person("Jakob", "Bossek", email = "j.bossek@gmail.com", role =
c("aut", "cre")))
Maintainer: Jakob Bossek <j.bossek@gmail.com>
URL: https://github.com/jakobbossek/cmaesr
BugReports: https://github.com/jakobbossek/cmaesr/issues
License: BSD_2_clause + file LICENSE
Depends: ParamHelpers (>= 1.3), BBmisc (>= 1.6), checkmate (>= 1.1),
smoof (>= 1.1)
Imports: ggplot2
Suggests: testthat
ByteCompile: yes
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2016-01-19 13:06:25 UTC; jboss
Author: Jakob Bossek [aut, cre]
Repository: CRAN
Date/Publication: 2016-01-19 15:08:02

● Data Source: CranContrib
● 0 images, 16 functions, 0 datasets
● Reverse Depends: 0

BatchJobs : Batch Computing with R

Package: BatchJobs
Title: Batch Computing with R
Description: Provides Map, Reduce and Filter variants to generate jobs on batch
computing systems like PBS/Torque, LSF, SLURM and Sun Grid Engine.
Multicore and SSH systems are also supported. For further details see the
project web page.
Author: Bernd Bischl <bernd_bischl@gmx.net>,
Michel Lang <michellang@gmail.com>,
Henrik Bengtsson <henrikb@braju.com>
Maintainer: Bernd Bischl <bernd_bischl@gmx.net>
URL: https://github.com/tudo-r/BatchJobs
BugReports: https://github.com/tudo-r/BatchJobs/issues
MailingList: batchjobs@googlegroups.com
License: BSD_2_clause + file LICENSE
Depends: R (>= 2.15.0), BBmisc (>= 1.9), methods
Imports: brew, checkmate (>= 1.5.1), DBI, digest, fail (>= 1.2),
parallel, RSQLite (>= 1.0.0), sendmailR, stats, stringr, utils
Suggests: MASS, testthat
LazyData: yes
ByteCompile: yes
Version: 1.6
Packaged: 2015-03-18 16:40:05 UTC; bischl
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2015-03-18 18:01:21

● Data Source: CranContrib
● Cran Task View: HighPerformanceComputing
● 0 images, 79 functions, 0 datasets
● Reverse Depends: 1

flacco : Feature-Based Landscape Analysis of Continuous and Constraint Optimization Problems

Package: flacco
Title: Feature-Based Landscape Analysis of Continuous and Constraint
Optimization Problems
Description: Contains tools and features, which can be used for an exploratory
landscape analysis of continuous optimization problems. Those are able to
quantify rather complex properties, such as the global structure,
separability, etc., of continuous optimization problems.
Authors@R: c(person("Pascal", "Kerschke", role = c("aut", "cre"),
email = "kerschke@uni-muenster.de"),
person("Jan", "Dagefoerde", role = "aut"))
URL: https://github.com/kerschke/flacco
BugReports: https://github.com/kerschke/flacco/issues
License: BSD_2_clause + file LICENSE
Encoding: UTF-8
Depends: R (>= 3.0.0), BBmisc, checkmate
Suggests: devtools, e1071, expm, lhs, MASS, Matrix, mda, mlbench, mlr,
numDeriv, parallel, parallelMap, plyr, RANN, rpart, shape,
smoof, testthat
LazyData: yes
ByteCompile: yes
Version: 1.3
Date: 2016-04-04
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2016-04-18 12:13:11 UTC; Pascal
Author: Pascal Kerschke [aut, cre],
Jan Dagefoerde [aut]
Maintainer: Pascal Kerschke <kerschke@uni-muenster.de>
Repository: CRAN
Date/Publication: 2016-04-19 00:32:03

● Data Source: CranContrib
● 0 images, 15 functions, 0 datasets
● Reverse Depends: 0

smoof : Single and Multi-Objective Optimization Test Functions

Package: smoof
Type: Package
Title: Single and Multi-Objective Optimization Test Functions
Description: Provides generators for a high number of both single- and multi-
objective test functions which are frequently used for the benchmarking of
(numerical) optimization algorithms. Moreover, it offers a set of convenient
functions to generate, plot and work with objective functions.
Version: 1.3
Date: 2016-02-23
Authors@R: c(person("Jakob", "Bossek", email = "j.bossek@gmail.com", role =
c("aut", "cre")), person("Pascal", "Kerschke", email = "kerschke@uni-muenster.de",
role = "ctb"))
URL: https://github.com/jakobbossek/smoof
BugReports: https://github.com/jakobbossek/smoof/issues
License: BSD_2_clause + file LICENSE
Depends: ParamHelpers (>= 1.3), BBmisc (>= 1.6), checkmate (>= 1.1)
Imports: ggplot2, RColorBrewer, plot3D, mco, Rcpp (>= 0.11.0)
Suggests: testthat, rPython (>= 0.0-5)
LazyData: yes
ByteCompile: yes
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 5.0.1
NeedsCompilation: yes
Packaged: 2016-02-23 15:36:32 UTC; jboss
Author: Jakob Bossek [aut, cre],
Pascal Kerschke [ctb]
Maintainer: Jakob Bossek <j.bossek@gmail.com>
Repository: CRAN
Date/Publication: 2016-03-01 17:15:35

● Data Source: CranContrib
● 0 images, 133 functions, 0 datasets
● Reverse Depends: 1

rpn : Converter and Interpreter for Reverse Polish Notation Expressions

Package: rpn
Type: Package
Title: Converter and Interpreter for Reverse Polish Notation
Expressions
Description: Pure R implementation of a simple (Reverse) Polish Notation (RPN) interpreter
and converter.
Version: 1.0
Date: 2016-06-06
Authors@R: c(person("Jakob", "Bossek", email = "j.bossek@gmail.com", role =
c("aut", "cre")))
Maintainer: Jakob Bossek <j.bossek@gmail.com>
URL: https://github.com/jakobbossek/rpn
BugReports: https://github.com/jakobbossek/rpn/issues
License: BSD_2_clause + file LICENSE
Depends: BBmisc (>= 1.6), checkmate (>= 1.1),
Suggests: testthat
ByteCompile: yes
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2016-06-07 13:53:54 UTC; jboss
Author: Jakob Bossek [aut, cre]
Repository: CRAN
Date/Publication: 2016-06-07 16:36:19

● Data Source: CranContrib
● 0 images, 1 functions, 0 datasets
● Reverse Depends: 0