Man pages for mlr
Machine Learning in R

addRRMeasure	Compute new measures for existing ResampleResult
Aggregation	Aggregation object.
aggregations	Aggregation methods.
agri.task	European Union Agricultural Workforces clustering task.
analyzeFeatSelResult	Show and visualize the steps of feature selection.
asROCRPrediction	Converts predictions to a format package ROCR can handle.
batchmark	Run machine learning benchmarks as distributed experiments.
bc.task	Wisconsin Breast Cancer classification task.
benchmark	Benchmark experiment for multiple learners and tasks.
BenchmarkResult	BenchmarkResult object.
bh.task	Boston Housing regression task.
cache_helpers	Get or delete mlr cache directory
calculateConfusionMatrix	Confusion matrix.
calculateROCMeasures	Calculate receiver operator measures.
capLargeValues	Convert large/infinite numeric values in a data.frame or...
changeData	Change Task Data
checkLearner	Exported for internal use only.
checkPredictLearnerOutput	Check output returned by predictLearner.
ClassifTask	Create a classification task.
ClusterTask	Create a cluster task.
configureMlr	Configures the behavior of the package.
ConfusionMatrix	Confusion matrix
convertBMRToRankMatrix	Convert BenchmarkResult to a rank-matrix.
convertMLBenchObjToTask	Convert a machine learning benchmark / demo object from...
costiris.task	Iris cost-sensitive classification task.
CostSensTask	Create a cost-sensitive classification task.
createDummyFeatures	Generate dummy variables for factor features.
createSpatialResamplingPlots	Create (spatial) resampling plot objects.
crossover	Crossover.
downsample	Downsample (subsample) a task or a data.frame.
dropFeatures	Drop some features of task.
estimateRelativeOverfitting	Estimate relative overfitting.
estimateResidualVariance	Estimate the residual variance.
extractFDABsignal	Bspline mlq features
extractFDADTWKernel	DTW kernel features
extractFDAFeatures	Extract features from functional data.
extractFDAFourier	Fast Fourier transform features.
extractFDAFPCA	Extract functional principal component analysis features.
extractFDAMultiResFeatures	Multiresolution feature extraction.
extractFDATsfeatures	Time-Series Feature Heuristics
extractFDAWavelets	Discrete Wavelet transform features.
FailureModel	Failure model.
FeatSelControl	Create control structures for feature selection.
FeatSelResult	Result of feature selection.
filterFeatures	Filter features by thresholding filter values.
friedmanPostHocTestBMR	Perform a posthoc Friedman-Nemenyi test.
friedmanTestBMR	Perform overall Friedman test for a BenchmarkResult.
fuelsubset.task	FuelSubset functional data regression task.
generateCalibrationData	Generate classifier calibration data.
generateCritDifferencesData	Generate data for critical-differences plot.
generateFeatureImportanceData	Generate feature importance.
generateFilterValuesData	Calculates feature filter values.
generateHyperParsEffectData	Generate hyperparameter effect data.
generateLearningCurveData	Generates a learning curve.
generatePartialDependenceData	Generate partial dependence.
generateThreshVsPerfData	Generate threshold vs. performance(s) for 2-class...
getBMRAggrPerformances	Extract the aggregated performance values from a benchmark...
getBMRFeatSelResults	Extract the feature selection results from a benchmark...
getBMRFilteredFeatures	Extract the feature selection results from a benchmark...
getBMRLearnerIds	Return learner ids used in benchmark.
getBMRLearners	Return learners used in benchmark.
getBMRLearnerShortNames	Return learner short.names used in benchmark.
getBMRMeasureIds	Return measures IDs used in benchmark.
getBMRMeasures	Return measures used in benchmark.
getBMRModels	Extract all models from benchmark result.
getBMRPerformances	Extract the test performance values from a benchmark result.
getBMRPredictions	Extract the predictions from a benchmark result.
getBMRTaskDescriptions	Extract all task descriptions from benchmark result...
getBMRTaskDescs	Extract all task descriptions from benchmark result.
getBMRTaskIds	Return task ids used in benchmark.
getBMRTuneResults	Extract the tuning results from a benchmark result.
getCaretParamSet	Get tuning parameters from a learner of the caret R-package.
getClassWeightParam	Get the class weight parameter of a learner.
getConfMatrix	Confusion matrix.
getDefaultMeasure	Get default measure.
getFailureModelDump	Return the error dump of FailureModel.
getFailureModelMsg	Return error message of FailureModel.
getFeatSelResult	Returns the selected feature set and optimization path after...
getFeatureImportance	Calculates feature importance values for trained models.
getFeatureImportanceLearner	Calculates feature importance values for a given learner.
getFilteredFeatures	Returns the filtered features.
getFunctionalFeatures	Get only functional features from a task or a data.frame.
getHomogeneousEnsembleModels	Deprecated, use 'getLearnerModel' instead.
getHyperPars	Get current parameter settings for a learner.
getLearnerId	Get the ID of the learner.
getLearnerModel	Get underlying R model of learner integrated into mlr.
getLearnerNote	Get the note for the learner.
getLearnerPackages	Get the required R packages of the learner.
getLearnerParamSet	Get the parameter set of the learner.
getLearnerParVals	Get the parameter values of the learner.
getLearnerPredictType	Get the predict type of the learner.
getLearnerShortName	Get the short name of the learner.
getLearnerType	Get the type of the learner.
getMlrOptions	Returns a list of mlr's options.
getMultilabelBinaryPerformances	Retrieve binary classification measures for multilabel...
getNestedTuneResultsOptPathDf	Get the 'opt.path's from each tuning step from the outer...
getNestedTuneResultsX	Get the tuned hyperparameter settings from a nested tuning.
getOOBPreds	Extracts out-of-bag predictions from trained models.
getOOBPredsLearner	Provides out-of-bag predictions for a given model and the...
getParamSet	Get a description of all possible parameter settings for a...
getPredictionDump	Return the error dump of a failed Prediction.
getPredictionProbabilities	Get probabilities for some classes.
getPredictionResponse	Get response / truth from prediction object.
getPredictionTaskDesc	Get summarizing task description from prediction.
getProbabilities	Deprecated, use 'getPredictionProbabilities' instead.
getResamplingIndices	Get the resampling indices from a tuning or feature selection...
getRRDump	Return the error dump of ResampleResult.
getRRPredictionList	Get list of predictions for train and test set of each single...
getRRPredictions	Get predictions from resample results.
getRRTaskDesc	Get task description from resample results (DEPRECATED).
getRRTaskDescription	Get task description from resample results (DEPRECATED).
getStackedBaseLearnerPredictions	Returns the predictions for each base learner.
getTaskClassLevels	Get the class levels for classification and multilabel tasks.
getTaskCosts	Extract costs in task.
getTaskData	Extract data in task.
getTaskDesc	Get a summarizing task description.
getTaskDescription	Deprecated, use getTaskDesc instead.
getTaskFeatureNames	Get feature names of task.
getTaskFormula	Get formula of a task.
getTaskId	Get the id of the task.
getTaskNFeats	Get number of features in task.
getTaskSize	Get number of observations in task.
getTaskTargetNames	Get the name(s) of the target column(s).
getTaskTargets	Get target data of task.
getTaskType	Get the type of the task.
getTuneResult	Returns the optimal hyperparameters and optimization path...
getTuneResultOptPath	Get the optimization path of a tuning result.
gunpoint.task	Gunpoint functional data classification task.
hasFunctionalFeatures	Check whether the object contains functional features.
hasProperties	Deprecated, use 'hasLearnerProperties' instead.
helpLearner	Access help page of learner functions.
helpLearnerParam	Get specific help for a learner's parameters.
imputations	Built-in imputation methods.
impute	Impute and re-impute data
iris.task	Iris classification task.
isFailureModel	Is the model a FailureModel?
joinClassLevels	Join some class existing levels to new, larger class levels...
learnerArgsToControl	Convert arguments to control structure.
LearnerProperties	Query properties of learners.
learners	List of supported learning algorithms.
listFilterEnsembleMethods	List ensemble filter methods.
listFilterMethods	List filter methods.
listLearnerProperties	List the supported learner properties
listLearners	Find matching learning algorithms.
listMeasureProperties	List the supported measure properties.
listMeasures	Find matching measures.
listTaskTypes	List the supported task types in mlr
lung.task	NCCTG Lung Cancer survival task.
makeAggregation	Specify your own aggregation of measures.
makeBaggingWrapper	Fuse learner with the bagging technique.
makeBaseWrapper	Exported for internal use only.
makeChainModel	Only exported for internal use.
makeClassificationViaRegressionWrapper	Classification via regression wrapper.
makeConstantClassWrapper	Wraps a classification learner to support problems where the...
makeCostMeasure	Creates a measure for non-standard misclassification costs.
makeCostSensClassifWrapper	Wraps a classification learner for use in cost-sensitive...
makeCostSensRegrWrapper	Wraps a regression learner for use in cost-sensitive...
makeCostSensWeightedPairsWrapper	Wraps a classifier for cost-sensitive learning to produce a...
makeCustomResampledMeasure	Construct your own resampled performance measure.
makeDownsampleWrapper	Fuse learner with simple downsampling (subsampling).
makeDummyFeaturesWrapper	Fuse learner with dummy feature creator.
makeExtractFDAFeatMethod	Constructor for FDA feature extraction methods.
makeExtractFDAFeatsWrapper	Fuse learner with an extractFDAFeatures method.
makeFeatSelWrapper	Fuse learner with feature selection.
makeFilter	Create a feature filter.
makeFilterEnsemble	Create an ensemble feature filter.
makeFilterWrapper	Fuse learner with a feature filter method.
makeFixedHoldoutInstance	Generate a fixed holdout instance for resampling.
makeFunctionalData	Create a data.frame containing functional features from a...
makeImputeMethod	Create a custom imputation method.
makeImputeWrapper	Fuse learner with an imputation method.
makeLearner	Create learner object.
makeLearners	Create multiple learners at once.
makeMeasure	Construct performance measure.
makeModelMultiplexer	Create model multiplexer for model selection to tune over...
makeModelMultiplexerParamSet	Creates a parameter set for model multiplexer tuning.
makeMulticlassWrapper	Fuse learner with multiclass method.
makeMultilabelBinaryRelevanceWrapper	Use binary relevance method to create a multilabel learner.
makeMultilabelClassifierChainsWrapper	Use classifier chains method (CC) to create a multilabel...
makeMultilabelDBRWrapper	Use dependent binary relevance method (DBR) to create a...
makeMultilabelNestedStackingWrapper	Use nested stacking method to create a multilabel learner.
makeMultilabelStackingWrapper	Use stacking method (stacked generalization) to create a...
makeOverBaggingWrapper	Fuse learner with the bagging technique and oversampling for...
makePreprocWrapper	Fuse learner with preprocessing.
makePreprocWrapperCaret	Fuse learner with preprocessing.
makeRemoveConstantFeaturesWrapper	Fuse learner with removal of constant features preprocessing.
makeResampleDesc	Create a description object for a resampling strategy.
makeResampleInstance	Instantiates a resampling strategy object.
makeRLearner.classif.fdausc.glm	Classification of functional data by Generalized Linear...
makeRLearner.classif.fdausc.kernel	Learner for kernel classification for functional data.
makeRLearner.classif.fdausc.np	Learner for nonparametric classification for functional data.
makeSMOTEWrapper	Fuse learner with SMOTE oversampling for imbalancy correction...
makeStackedLearner	Create a stacked learner object.
makeTaskDesc	Exported for internal use.
makeTaskDescInternal	Exported for internal use.
makeTuneControlCMAES	Create control object for hyperparameter tuning with CMAES.
makeTuneControlDesign	Create control object for hyperparameter tuning with...
makeTuneControlGenSA	Create control object for hyperparameter tuning with GenSA.
makeTuneControlGrid	Create control object for hyperparameter tuning with grid...
makeTuneControlIrace	Create control object for hyperparameter tuning with Irace.
makeTuneControlMBO	Create control object for hyperparameter tuning with MBO.
makeTuneControlRandom	Create control object for hyperparameter tuning with random...
makeTuneWrapper	Fuse learner with tuning.
makeUndersampleWrapper	Fuse learner with simple ove/underrsampling for imbalancy...
makeWeightedClassesWrapper	Wraps a classifier for weighted fitting where each class...
makeWrappedModel	Induced model of learner.
MeasureProperties	Query properties of measures.
measures	Performance measures.
mergeBenchmarkResults	Merge different BenchmarkResult objects.
mergeSmallFactorLevels	Merges small levels of factors into new level.
mlrFamilies	mlr documentation families
mlr-package	mlr: Machine Learning in R
mtcars.task	Motor Trend Car Road Tests clustering task.
MultilabelTask	Create a multilabel task.
normalizeFeatures	Normalize features.
oversample	Over- or undersample binary classification task to handle...
parallelization	Supported parallelization methods
performance	Measure performance of prediction.
phoneme.task	Phoneme functional data multilabel classification task.
pid.task	PimaIndiansDiabetes classification task.
plotBMRBoxplots	Create box or violin plots for a BenchmarkResult.
plotBMRRanksAsBarChart	Create a bar chart for ranks in a BenchmarkResult.
plotBMRSummary	Plot a benchmark summary.
plotCalibration	Plot calibration data using ggplot2.
plotCritDifferences	Plot critical differences for a selected measure.
plotFilterValues	Plot filter values using ggplot2.
plotHyperParsEffect	Plot the hyperparameter effects data
plotLearnerPrediction	Visualizes a learning algorithm on a 1D or 2D data set.
plotLearningCurve	Plot learning curve data using ggplot2.
plotPartialDependence	Plot a partial dependence with ggplot2.
plotResiduals	Create residual plots for prediction objects or benchmark...
plotROCCurves	Plots a ROC curve using ggplot2.
plotThreshVsPerf	Plot threshold vs. performance(s) for 2-class classification...
plotTuneMultiCritResult	Plots multi-criteria results after tuning using ggplot2.
Prediction	Prediction object.
predictLearner	Predict new data with an R learner.
predict.WrappedModel	Predict new data.
reduceBatchmarkResults	Reduce results of a batch-distributed benchmark.
reextractFDAFeatures	Re-extract features from a data set
RegrTask	Create a regression task.
reimpute	Re-impute a data set
removeConstantFeatures	Remove constant features from a data set.
removeHyperPars	Remove hyperparameters settings of a learner.
resample	Fit models according to a resampling strategy.
ResamplePrediction	Prediction from resampling.
ResampleResult	ResampleResult object.
RLearner	Internal construction / wrapping of learner object.
selectFeatures	Feature selection by wrapper approach.
setAggregation	Set aggregation function of measure.
setHyperPars	Set the hyperparameters of a learner object.
setHyperPars2	Only exported for internal use.
setId	Set the id of a learner object.
setLearnerId	Set the ID of a learner object.
setMeasurePars	Set parameters of performance measures
setPredictThreshold	Set the probability threshold the learner should use.
setPredictType	Set the type of predictions the learner should return.
setThreshold	Set threshold of prediction object.
simplifyMeasureNames	Simplify measure names.
smote	Synthetic Minority Oversampling Technique to handle class...
sonar.task	Sonar classification task.
spam.task	Spam classification task.
spatial.task	J. Muenchow's Ecuador landslide data set
subsetTask	Subset data in task.
summarizeColumns	Summarize columns of data.frame or task.
summarizeLevels	Summarizes factors of a data.frame by tabling them.
SurvTask	Create a survival task.
Task	Create a classification, regression, survival, cluster,...
TaskDesc	Description object for task.
train	Train a learning algorithm.
trainLearner	Train an R learner.
TuneControl	Control object for tuning
TuneMultiCritControl	Create control structures for multi-criteria tuning.
TuneMultiCritResult	Result of multi-criteria tuning.
tuneParams	Hyperparameter tuning.
tuneParamsMultiCrit	Hyperparameter tuning for multiple measures at once.
TuneResult	Result of tuning.
tuneThreshold	Tune prediction threshold.
wpbc.task	Wisonsin Prognostic Breast Cancer (WPBC) survival task.
yeast.task	Yeast multilabel classification task.