Other packages > Find by keyword >

mlr  

Machine Learning in R
View on CRAN: Click here


Download and install mlr package within the R console
Install from CRAN:
install.packages("mlr")

Install from Github:
library("remotes")
install_github("cran/mlr")

Install by package version:
library("remotes")
install_version("mlr", "2.19.3")



Attach the package and use:
library("mlr")
Maintained by
Martin Binder
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2013-08-30
Latest Update: 2025-09-03
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.
How to cite:
Martin Binder (2013). mlr: Machine Learning in R. R package version 2.19.3, https://cran.r-project.org/web/packages/mlr. Accessed 15 Sep. 2026.
Previous versions and publish date:
(2026-07-09 06:31), 1.1-18 (2013-08-30 01:32), 2.0 (2014-07-04 02:25), 2.1 (2014-07-21 20:08), 2.2 (2014-10-29 07:43), 2.3 (2015-02-04 07:43), 2.4 (2015-06-13 00:40), 2.5 (2015-11-20 17:38), 2.6 (2015-11-26 08:38), 2.7 (2015-12-04 15:58), 2.8 (2016-02-13 08:37), 2.9 (2016-08-03 18:03), 2.10 (2017-02-07 10:08), 2.11 (2017-03-15 08:49), 2.12.1 (2018-03-29 12:03), 2.12 (2018-03-11 01:07), 2.13 (2018-08-28 14:30), 2.14.0 (2019-04-26 00:00), 2.15.0 (2019-08-06 17:10), 2.16.0 (2019-11-26 15:50), 2.17.0 (2020-01-10 21:00), 2.17.1 (2020-03-24 11:40), 2.18.0 (2020-10-05 12:20), 2.19.0 (2021-02-22 15:50), 2.19.1 (2022-09-29 15:30), 2.19.2 (2024-06-12 12:50)
Other packages that cited mlr R package
View mlr citation profile
Other R packages that mlr depends, imports, suggests or enhances
Complete documentation for mlr
Functions, R codes and Examples using the mlr R package
Some associated functions: Aggregation . BenchmarkResult . ClassifTask . ClusterTask . ConfusionMatrix . CostSensTask . FailureModel . FeatSelControl . FeatSelResult . LearnerProperties . MeasureProperties . MultilabelTask . Prediction . RLearner . RegrTask . ResamplePrediction . ResampleResult . SurvTask . Task . TaskDesc . TuneControl . TuneMultiCritControl . TuneMultiCritResult . TuneResult . addRRMeasure . aggregations . agri.task . analyzeFeatSelResult . asROCRPrediction . batchmark . bc.task . benchmark . bh.task . cache_helpers . calculateConfusionMatrix . calculateROCMeasures . capLargeValues . changeData . checkLearner . checkPredictLearnerOutput . configureMlr . convertBMRToRankMatrix . convertMLBenchObjToTask . costiris.task . createDummyFeatures . createSpatialResamplingPlots . crossover . downsample . dropFeatures . estimateRelativeOverfitting . estimateResidualVariance . extractFDABsignal . extractFDADTWKernel . extractFDAFPCA . extractFDAFeatures . extractFDAFourier . extractFDAMultiResFeatures . extractFDATsfeatures . extractFDAWavelets . filterFeatures . friedmanPostHocTestBMR . friedmanTestBMR . fuelsubset.task . generateCalibrationData . generateCritDifferencesData . generateFeatureImportanceData . generateFilterValuesData . generateHyperParsEffectData . generateLearningCurveData . generatePartialDependenceData . generateThreshVsPerfData . getBMRAggrPerformances . getBMRFeatSelResults . getBMRFilteredFeatures . getBMRLearnerIds . getBMRLearnerShortNames . getBMRLearners . getBMRMeasureIds . getBMRMeasures . getBMRModels . getBMRPerformances . getBMRPredictions . getBMRTaskDescriptions . getBMRTaskDescs . getBMRTaskIds . getBMRTuneResults . getCaretParamSet . getClassWeightParam . getConfMatrix . getDefaultMeasure . getFailureModelDump . getFailureModelMsg . getFeatSelResult . getFeatureImportance . getFeatureImportanceLearner . getFilteredFeatures . getFunctionalFeatures . getHomogeneousEnsembleModels . getHyperPars . getLearnerId . getLearnerModel . getLearnerNote . getLearnerPackages . getLearnerParVals . getLearnerParamSet . getLearnerPredictType . getLearnerShortName . getLearnerType . getMlrOptions . getMultilabelBinaryPerformances . getNestedTuneResultsOptPathDf . getNestedTuneResultsX . getOOBPreds . getOOBPredsLearner . getParamSet . getPredictionDump . getPredictionProbabilities . getPredictionResponse . getPredictionTaskDesc . getProbabilities . getRRDump . getRRPredictionList . getRRPredictions . getRRTaskDesc . getRRTaskDescription . getResamplingIndices . getStackedBaseLearnerPredictions . getTaskClassLevels . getTaskCosts . getTaskData . getTaskDesc . getTaskDescription . getTaskFeatureNames . getTaskFormula . getTaskId . getTaskNFeats . getTaskSize . getTaskTargetNames . getTaskTargets . getTaskType . getTuneResult . getTuneResultOptPath . gunpoint.task . hasFunctionalFeatures . hasProperties . helpLearner . helpLearnerParam . imputations . impute . iris.task . isFailureModel . joinClassLevels . learnerArgsToControl . learners . listFilterEnsembleMethods . listFilterMethods . listLearnerProperties . listLearners . listMeasureProperties . listMeasures . listTaskTypes . lung.task . makeAggregation . makeBaggingWrapper . makeBaseWrapper . makeChainModel . makeClassificationViaRegressionWrapper . makeConstantClassWrapper . makeCostMeasure . makeCostSensClassifWrapper . makeCostSensRegrWrapper . makeCostSensWeightedPairsWrapper . makeCustomResampledMeasure . makeDownsampleWrapper . makeDummyFeaturesWrapper . makeExtractFDAFeatMethod . makeExtractFDAFeatsWrapper . makeFeatSelWrapper . makeFilter . makeFilterEnsemble . makeFilterWrapper . makeFixedHoldoutInstance . makeFunctionalData . makeImputeMethod . makeImputeWrapper . makeLearner . makeLearners . makeMeasure . makeModelMultiplexer . makeModelMultiplexerParamSet . makeMulticlassWrapper . makeMultilabelBinaryRelevanceWrapper . makeMultilabelClassifierChainsWrapper . makeMultilabelDBRWrapper . makeMultilabelNestedStackingWrapper . makeMultilabelStackingWrapper . makeOverBaggingWrapper . makePreprocWrapper . makePreprocWrapperCaret . makeRLearner.classif.fdausc.glm . makeRLearner.classif.fdausc.kernel . makeRLearner.classif.fdausc.np . makeRemoveConstantFeaturesWrapper . makeResampleDesc . makeResampleInstance . makeSMOTEWrapper . makeStackedLearner . makeTaskDesc . makeTaskDescInternal . makeTuneControlCMAES . makeTuneControlDesign . makeTuneControlGenSA . makeTuneControlGrid . makeTuneControlIrace . makeTuneControlMBO . makeTuneControlRandom . makeTuneWrapper . makeUndersampleWrapper . makeWeightedClassesWrapper . makeWrappedModel . measures . mergeBenchmarkResults . mergeSmallFactorLevels . mlr-package . mlrFamilies . mtcars.task . normalizeFeatures . oversample . parallelization . performance . phoneme.task . pid.task . plotBMRBoxplots . plotBMRRanksAsBarChart . plotBMRSummary . plotCalibration . plotCritDifferences . plotFilterValues . plotHyperParsEffect . plotLearnerPrediction . plotLearningCurve . plotPartialDependence . plotROCCurves . plotResiduals . plotThreshVsPerf . plotTuneMultiCritResult . predict.WrappedModel . predictLearner . reduceBatchmarkResults . reextractFDAFeatures . reimpute . removeConstantFeatures . removeHyperPars . resample . selectFeatures . setAggregation . setHyperPars . setHyperPars2 . setId . setLearnerId . setMeasurePars . setPredictThreshold . setPredictType . setThreshold . simplifyMeasureNames . smote . sonar.task . spam.task . spatial.task . subsetTask . summarizeColumns . summarizeLevels . train . trainLearner . tuneParams . tuneParamsMultiCrit . tuneThreshold . wpbc.task . yeast.task . 
Some associated R codes: Aggregation.R . BaggingWrapper.R . BaseEnsemble.R . BaseEnsemble_operators.R . BaseWrapper.R . BaseWrapper_operators.R . BenchmarkResultOrderLevels.R . BenchmarkResult_operators.R . ChainModel.R . ChainModel_operators.R . ClassifTask.R . ClassificationViaRegressionWrapper.R . ClusterTask.R . ConstantClassWrapper.R . CostSensClassifWrapper.R . CostSensRegrWrapper.R . CostSensTask.R . CostSensWeightedPairsWrapper.R . DownsampleWrapper.R . DummyFeaturesWrapper.R . FailureModel.R . FeatSelControl.R . FeatSelControlExhaustive.R . FeatSelControlGA.R . FeatSelControlRandom.R . FeatSelControlSequential.R . FeatSelResult.R . FeatSelWrapper.R . Filter.R . FilterEnsemble.R . FilterWrapper.R . HoldoutInstance_make_fixed.R . HomogeneousEnsemble.R . Impute.R . ImputeMethods.R . ImputeWrapper.R . Learner.R . Learner_operators.R . Learner_properties.R . Measure.R . Measure_colAUC.R . Measure_custom_resampled.R . Measure_make_cost.R . Measure_operators.R . Measure_properties.R . ModelMultiplexer.R . ModelMultiplexerParamSet.R . MulticlassWrapper.R . MultilabelBinaryRelevanceWrapper.R . MultilabelClassifierChainsWrapper.R . MultilabelDBRWrapper.R . MultilabelNestedStackingWrapper.R . MultilabelStackingWrapper.R . MultilabelTask.R . NoFeaturesModel.R . OptControl.R . OptResult.R . OptWrapper.R . OverBaggingWrapper.R . OverUnderSampling.R . OverUndersampleWrapper.R . Prediction.R . Prediction_operators.R . PreprocWrapper.R . PreprocWrapperCaret.R . RLearner.R . RLearner_classif_C50.R . RLearner_classif_FDboost.R . RLearner_classif_IBk.R . RLearner_classif_J48.R . RLearner_classif_JRip.R . RLearner_classif_LiblineaRL1L2SVC.R . RLearner_classif_LiblineaRL1LogReg.R . RLearner_classif_LiblineaRL2L1SVC.R . RLearner_classif_LiblineaRL2LogReg.R . RLearner_classif_LiblineaRL2SVC.R . RLearner_classif_LiblineaRMultiClassSVC.R . RLearner_classif_OneR.R . RLearner_classif_PART.R . RLearner_classif_RRF.R . RLearner_classif_ada.R . RLearner_classif_adaboostm1.R . RLearner_classif_bartMachine.R . RLearner_classif_binomial.R . RLearner_classif_boosting.R . RLearner_classif_bst.R . RLearner_classif_cforest.R . RLearner_classif_clusterSVM.R . RLearner_classif_ctree.R . RLearner_classif_cvglmnet.R . RLearner_classif_dbnDNN.R . RLearner_classif_dcSVM.R . RLearner_classif_earth.R . RLearner_classif_evtree.R . RLearner_classif_fdausc.glm.R . RLearner_classif_fdausc.kernel.R . RLearner_classif_fdausc.knn.R . RLearner_classif_fdausc.np.R . RLearner_classif_featureless.R . RLearner_classif_fgam.R . RLearner_classif_fnn.R . RLearner_classif_gamboost.R . RLearner_classif_gaterSVM.R . RLearner_classif_gausspr.R . RLearner_classif_gbm.R . RLearner_classif_glmboost.R . RLearner_classif_glmnet.R . RLearner_classif_h2odeeplearning.R . RLearner_classif_h2ogbm.R . RLearner_classif_h2oglm.R . RLearner_classif_h2orandomForest.R . RLearner_classif_kknn.R . RLearner_classif_knn.R . RLearner_classif_ksvm.R . RLearner_classif_lda.R . RLearner_classif_logreg.R . RLearner_classif_lssvm.R . RLearner_classif_lvq1.R . RLearner_classif_mda.R . RLearner_classif_mlp.R . RLearner_classif_multinom.R . RLearner_classif_naiveBayes.R . RLearner_classif_neuralnet.R . RLearner_classif_nnTrain.R . RLearner_classif_nnet.R . RLearner_classif_pamr.R . RLearner_classif_penalized.R . RLearner_classif_plr.R . RLearner_classif_plsdaCaret.R . RLearner_classif_probit.R . RLearner_classif_qda.R . RLearner_classif_rFerns.R . RLearner_classif_randomForest.R . RLearner_classif_ranger.R . RLearner_classif_rda.R . RLearner_classif_rotationForest.R . RLearner_classif_rpart.R . RLearner_classif_saeDNN.R . RLearner_classif_sda.R . RLearner_classif_sparseLDA.R . RLearner_classif_svm.R . RLearner_classif_xgboost.R . RLearner_cluster_Cobweb.R . RLearner_cluster_EM.R . RLearner_cluster_FarthestFirst.R . RLearner_cluster_MiniBatchKmeans.R . RLearner_cluster_SimpleKMeans.R . RLearner_cluster_XMeans.R . RLearner_cluster_cmeans.R . RLearner_cluster_dbscan.R . RLearner_cluster_kkmeans.R . RLearner_cluster_kmeans.R . RLearner_multilabel_cforest.R . RLearner_multilabel_rFerns.R . RLearner_regr_FDboost.R . RLearner_regr_GPfit.R . RLearner_regr_IBk.R . RLearner_regr_LiblineaRL2L1SVR.R . RLearner_regr_LiblineaRL2L2SVR.R . RLearner_regr_RRF.R . RLearner_regr_bartMachine.R . RLearner_regr_bcart.R . RLearner_regr_bgp.R . RLearner_regr_bgpllm.R . RLearner_regr_blm.R . RLearner_regr_brnn.R . RLearner_regr_bst.R . RLearner_regr_btgp.R . RLearner_regr_btgpllm.R . RLearner_regr_btlm.R . RLearner_regr_cforest.R . RLearner_regr_crs.R . RLearner_regr_ctree.R . RLearner_regr_cubist.R . RLearner_regr_cvglmnet.R . RLearner_regr_earth.R . RLearner_regr_evtree.R . RLearner_regr_featureless.R . RLearner_regr_fgam.R . RLearner_regr_fnn.R . RLearner_regr_frbs.R . RLearner_regr_gamboost.R . RLearner_regr_gausspr.R . RLearner_regr_gbm.R . RLearner_regr_glm.R . RLearner_regr_glmboost.R . RLearner_regr_glmnet.R . RLearner_regr_h2odeeplearning.R . RLearner_regr_h2ogbm.R . RLearner_regr_h2oglm.R . RLearner_regr_h2orandomForest.R . RLearner_regr_kknn.R . RLearner_regr_km.R . RLearner_regr_ksvm.R . RLearner_regr_laGP.R . RLearner_regr_lm.R . RLearner_regr_mars.R . RLearner_regr_mob.R . RLearner_regr_nnet.R . RLearner_regr_pcr.R . RLearner_regr_penalized.R . RLearner_regr_plsr.R . RLearner_regr_randomForest.R . RLearner_regr_ranger.R . RLearner_regr_rpart.R . RLearner_regr_rsm.R . RLearner_regr_rvm.R . RLearner_regr_svm.R . RLearner_regr_xgboost.R . RLearner_surv_cforest.R . RLearner_surv_coxph.R . RLearner_surv_cvglmnet.R . RLearner_surv_gamboost.R . RLearner_surv_gbm.R . RLearner_surv_glmboost.R . RLearner_surv_glmnet.R . RLearner_surv_ranger.R . RLearner_surv_rpart.R . RegrTask.R . RemoveConstantFeaturesWrapper.R . ResampleDesc.R . ResampleInstance.R . ResampleInstances.R . ResamplePrediction.R . ResampleResult.R . ResampleResult_operators.R . SMOTEWrapper.R . StackedLearner.R . SupervisedTask.R . SurvTask.R . Task.R . TaskDesc.R . Task_operators.R . TuneControl.R . TuneControlCMAES.R . TuneControlDesign.R . TuneControlGenSA.R . TuneControlGrid.R . TuneControlIrace.R . TuneControlMBO.R . TuneControlRandom.R . TuneMultiCritControl.R . TuneMultiCritControlGrid.R . TuneMultiCritControlMBO.R . TuneMultiCritControlNSGA2.R . TuneMultiCritControlRandom.R . TuneMultiCritResult.R . TuneResult.R . TuneWrapper.R . UnsupervisedTask.R . WeightedClassesWrapper.R . WrappedModel.R . aggregations.R . analyzeFeatSelResult.R . asROCRPrediction.R . batchmark.R . benchmark.R . benchmark_helpers.R . cache_helpers.R . calculateConfusionMatrix.R . calculateROCMeasures.R . capLargeValues.R . checkAggrBeforeResample.R . checkBMRMeasure.R . checkLearner.R . checkLearnerBeforeTrain.R . checkMeasures.R . checkPrediction.R . checkTargetPreproc.R . checkTask.R . checkTaskSubset.R . checkTunerParset.R . configureMlr.R . convertBMRToRankMatrix.R . convertMLBenchObjToTask.R . convertX.R . createDummyFeatures.R . createSpatialResamplingPlots.R . crossover.R . datasets.R . downsample.R . dropFeatures.R . estimateResidualVariance.R . evalOptimizationState.R . extractFDAFeatures.R . extractFDAFeaturesMethods.R . extractFDAFeaturesWrapper.R . filterFeatures.R . fixDataForLearner.R . friedmanPostHocTestBMR.R . friedmanTestBMR.R . generateCalibration.R . generateFeatureImportance.R . generateFilterValues.R . generateHyperParsEffect.R . generateLearningCurve.R . generatePartialDependence.R . generateThreshVsPerf.R . getCaretParamSet.R . getClassWeightParam.R . getConfMatrix.R . getFeatSelResult.R . getFeatureImportance.R . getFunctionalFeatures.R . getHyperPars.R . getMultilabelBinaryPerformances.R . getNestedTuneResults.R . getOOBPreds.R . getParamSet.R . getResampleExtract.R . getResamplingIndices.R . getTaskConstructorForLearner.R . getTuneResult.R . getTuneThresholdExtra.R . hasFunctionalFeatures.R . helpLearner.R . helpers.R . helpers_FDGAMBoost.R . helpers_fda.R . joinClassLevels.R . learnerArgsToControl.R . learners.R . listLearners.R . listMeasures.R . logFunOpt.R . makeFunctionalData.R . makeLearner.R . makeLearners.R . measures.R . mergeBenchmarkResults.R . mergeSmallFactorLevels.R . mutateBits.R . normalizeFeatures.R . options.R . parallelization.R . performance.R . plotBMRBoxplots.R . plotBMRRanksAsBarChart.R . plotBMRSummary.R . plotCritDifferences.R . plotLearnerPrediction.R . plotResiduals.R . plotTuneMultiCritResult.R . predict.R . predictLearner.R . relativeOverfitting.R . removeConstantFeatures.R . removeHyperPars.R . resample.R . resample_convenience.R . selectFeatures.R . selectFeaturesExhaustive.R . selectFeaturesGA.R . selectFeaturesRandom.R . selectFeaturesSequential.R . setHyperPars.R . setId.R . setPredictThreshold.R . setPredictType.R . setThreshold.R . simplifyMeasureNames.R . smote.R . summarizeColumns.R . summarizeLevels.R . train.R . trainLearner.R . tuneCMAES.R . tuneDesign.R . tuneGenSA.R . tuneGrid.R . tuneIrace.R . tuneMBO.R . tuneMultiCritGrid.R . tuneMultiCritNSGA2.R . tuneMultiCritRandom.R . tuneParams.R . tuneParamsMultiCrit.R . tuneRandom.R . tuneThreshold.R . tunerFitnFun.R . utils.R . utils_imbalancy.R . utils_opt.R . utils_plot.R . zzz.R .  Full mlr package functions and examples
Downloads during the last 30 days

Today's Hot Picks in Authors and Packages

CTTinShiny  
Shiny Interface for the CTT Package
A Shiny interface developed in close coordination with the CTT package, providing a GUI that guides ...
Download / Learn more Package Citations See dependency  
objectSignals  
Observer Pattern for S4
A mutable Signal object can report changes to its state, clients could register functions so that t ...
Download / Learn more Package Citations See dependency  
functClust  
Functional Clustering of Redundant Components of a System
Cluster together the components that make up an interactivesystem on the basis of their functional r ...
Download / Learn more Package Citations See dependency  
SiER  
Signal Extraction Approach for Sparse Multivariate Response Regression
Methods for regression with high-dimensional predictors andunivariate or maltivariate response varia ...
Download / Learn more Package Citations See dependency  
AFR  
Toolkit for Regression Analysis of Kazakhstan Banking Sector Data
Tool is created for regression, prediction and forecast analysis of macroeconomic and credit data. ...
Download / Learn more Package Citations See dependency  
quickcode  
Quick and Essential 'R' Tricks for Better Scripts
The NOT functions, 'R' tricks and a compilation of some simple quick plus often used 'R' codes to im ...
Download / Learn more Package Citations See dependency  

28,565

R Packages

239,283

Dependencies

75,677

Author Associations

28,566

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA