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.
| Version: |
2.13 |
| Depends: |
R (≥ 3.0.2), ParamHelpers (≥ 1.10) |
| Imports: |
BBmisc (≥ 1.11), backports (≥ 1.1.0), ggplot2, stats, stringi, checkmate (≥ 1.8.2), data.table, methods, parallelMap (≥ 1.3), survival, utils, XML |
| Suggests: |
ada, adabag, bartMachine, batchtools, brnn, bst, C50, care, caret (≥ 6.0-57), class, clue, cluster, clusterSim (≥
0.44-5), clValid, cmaes, cowplot, CoxBoost, crs, Cubist, deepnet, DiceKriging, DiscriMiner, e1071, earth, elasticnet, emoa, evtree, extraTrees, fda.usc, FDboost, flare, FNN, fpc, frbs, FSelector, gbm, GenSA, glmnet, hrbrthemes, h2o (≥
3.6.0.8), GPfit, Hmisc, irace (≥ 2.0), kernlab, kknn, klaR, knitr, laGP, LiblineaR, lintr (≥ 1.0.0.9001), MASS, mboost, mco, mda, mlbench, mldr, mlrMBO, mmpf, modeltools, mRMRe, nnet, nodeHarvest (≥ 0.7-3), neuralnet, numDeriv, pamr, party, penalized (≥ 0.9-47), pls, PMCMR (≥ 4.1), purrr, randomForest, randomForestSRC (≥ 2.7.0), ranger (≥ 0.8.0), refund, rex, rFerns, rknn, rmarkdown, ROCR, rotationForest, rpart, RRF, rgenoud, rrlda, rsm, RSNNS, RWeka, sda, sf, smoof, sparseLDA, stepPlr, survAUC, svglite, SwarmSVM, testthat, tgp, TH.data, wavelets, xgboost (≥ 0.6-2) |
| Published: |
2018-08-28 |
| Author: |
Bernd Bischl  [aut, cre],
Michel Lang [aut],
Lars Kotthoff [aut],
Julia Schiffner [aut],
Jakob Richter [aut],
Zachary Jones [aut],
Giuseppe Casalicchio [aut],
Mason Gallo [aut],
Patrick Schratz [aut],
Jakob Bossek [ctb],
Erich Studerus [ctb],
Leonard Judt [ctb],
Tobias Kuehn [ctb],
Pascal Kerschke [ctb],
Florian Fendt [ctb],
Philipp Probst [ctb],
Xudong Sun [ctb],
Janek Thomas [ctb],
Bruno Vieira [ctb],
Laura Beggel [ctb],
Quay Au [ctb],
Martin Binder [ctb],
Florian Pfisterer [ctb],
Stefan Coors [ctb],
Steve Bronder [ctb],
Alexander Engelhardt [ctb],
Christoph Molnar [ctb] |
| Maintainer: |
Bernd Bischl <bernd_bischl at gmx.net> |
| BugReports: |
https://github.com/mlr-org/mlr/issues |
| License: |
BSD_2_clause + file LICENSE |
| URL: |
https://github.com/mlr-org/mlr |
| NeedsCompilation: |
yes |
| Citation: |
mlr citation info |
| Materials: |
NEWS |
| In views: |
MachineLearning |
| CRAN checks: |
mlr results |