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Package

mlr3pipelines mlr3pipelines-package
mlr3pipelines: Preprocessing Operators and Pipelines for 'mlr3'

Building Blocks

PipeOp
PipeOp Base Class
Graph
Graph Base Class
PipeOpTaskPreproc
Task Preprocessing Base Class
PipeOpTaskPreprocSimple
Simple Task Preprocessing Base Class
PipeOpImpute
Imputation Base Class
Multiplicity()
Multiplicity

Graph Tools

`%>>%` concat_graphs() `%>>!%`
PipeOp Composition Operator
gunion()
Disjoint Union of Graphs
greplicate()
Create Disjoint Graph Union of Copies of a Graph

PipeOps

mlr_pipeops
Dictionary of PipeOps
po() pos()
Shorthand PipeOp Constructor
mlr_pipeops_adas PipeOpADAS
ADAS Balancing
mlr_pipeops_blsmote PipeOpBLSmote
BLSMOTE Balancing
mlr_pipeops_boxcox PipeOpBoxCox
Box-Cox Transformation of Numeric Features
mlr_pipeops_branch PipeOpBranch
Path Branching
mlr_pipeops_chunk PipeOpChunk
Chunk Input into Multiple Outputs
mlr_pipeops_classbalancing PipeOpClassBalancing
Class Balancing
mlr_pipeops_classifavg PipeOpClassifAvg
Majority Vote Prediction
mlr_pipeops_classweights PipeOpClassWeights
Class Weights for Sample Weighting
mlr_pipeops_colapply PipeOpColApply
Apply a Function to each Column of a Task
mlr_pipeops_collapsefactors PipeOpCollapseFactors
Collapse Factors
mlr_pipeops_colroles PipeOpColRoles
Change Column Roles of a Task
mlr_pipeops_copy PipeOpCopy
Copy Input Multiple Times
mlr_pipeops_datefeatures PipeOpDateFeatures
Preprocess Date Features
mlr_pipeops_encode PipeOpEncode
Factor Encoding
mlr_pipeops_encodeimpact PipeOpEncodeImpact
Conditional Target Value Impact Encoding
mlr_pipeops_encodelmer PipeOpEncodeLmer
Impact Encoding with Random Intercept Models
mlr_pipeops_featureunion PipeOpFeatureUnion
Aggregate Features from Multiple Inputs
mlr_pipeops_filter PipeOpFilter
Feature Filtering
mlr_pipeops_fixfactors PipeOpFixFactors
Fix Factor Levels
mlr_pipeops_histbin PipeOpHistBin
Split Numeric Features into Equally Spaced Bins
mlr_pipeops_ica PipeOpICA
Independent Component Analysis
mlr_pipeops_imputeconstant PipeOpImputeConstant
Impute Features by a Constant
mlr_pipeops_imputehist PipeOpImputeHist
Impute Numerical Features by Histogram
mlr_pipeops_imputelearner PipeOpImputeLearner
Impute Features by Fitting a Learner
mlr_pipeops_imputemean PipeOpImputeMean
Impute Numerical Features by their Mean
mlr_pipeops_imputemedian PipeOpImputeMedian
Impute Numerical Features by their Median
mlr_pipeops_imputemode PipeOpImputeMode
Impute Features by their Mode
mlr_pipeops_imputeoor PipeOpImputeOOR
Out of Range Imputation
mlr_pipeops_imputesample PipeOpImputeSample
Impute Features by Sampling
mlr_pipeops_kernelpca PipeOpKernelPCA
Kernelized Principle Component Analysis
mlr_pipeops_learner PipeOpLearner
Wrap a Learner into a PipeOp
mlr_pipeops_learner_cv PipeOpLearnerCV
Wrap a Learner into a PipeOp with Cross-validated Predictions as Features
mlr_pipeops_missind PipeOpMissInd
Add Missing Indicator Columns
mlr_pipeops_modelmatrix PipeOpModelMatrix
Transform Columns by Constructing a Model Matrix
mlr_pipeops_multiplicityexply PipeOpMultiplicityExply
Explicate a Multiplicity
mlr_pipeops_multiplicityimply PipeOpMultiplicityImply
Implicate a Multiplicity
mlr_pipeops_mutate PipeOpMutate
Add Features According to Expressions
mlr_pipeops_nmf PipeOpNMF
Non-negative Matrix Factorization
mlr_pipeops_nop PipeOpNOP
Simply Push Input Forward
mlr_pipeops_ovrsplit PipeOpOVRSplit
Split a Classification Task into Binary Classification Tasks
mlr_pipeops_ovrunite PipeOpOVRUnite
Unite Binary Classification Tasks
mlr_pipeops_pca PipeOpPCA
Principle Component Analysis
mlr_pipeops_proxy PipeOpProxy
Wrap another PipeOp or Graph as a Hyperparameter
mlr_pipeops_quantilebin PipeOpQuantileBin
Split Numeric Features into Quantile Bins
mlr_pipeops_randomprojection PipeOpRandomProjection
Project Numeric Features onto a Randomly Sampled Subspace
mlr_pipeops_randomresponse PipeOpRandomResponse
Generate a Randomized Response Prediction
mlr_pipeops_regravg PipeOpRegrAvg
Weighted Prediction Averaging
mlr_pipeops_removeconstants PipeOpRemoveConstants
Remove Constant Features
mlr_pipeops_renamecolumns PipeOpRenameColumns
Rename Columns
mlr_pipeops_replicate PipeOpReplicate
Replicate the Input as a Multiplicity
mlr_pipeops_rowapply PipeOpRowApply
Apply a Function to each Row of a Task
mlr_pipeops_scale PipeOpScale
Center and Scale Numeric Features
mlr_pipeops_scalemaxabs PipeOpScaleMaxAbs
Scale Numeric Features with Respect to their Maximum Absolute Value
mlr_pipeops_scalerange PipeOpScaleRange
Linearly Transform Numeric Features to Match Given Boundaries
mlr_pipeops_select PipeOpSelect
Remove Features Depending on a Selector
mlr_pipeops_smote PipeOpSmote
SMOTE Balancing
mlr_pipeops_smotenc PipeOpSmoteNC
SMOTENC Balancing
mlr_pipeops_spatialsign PipeOpSpatialSign
Normalize Data Row-wise
mlr_pipeops_subsample PipeOpSubsample
Subsampling
mlr_pipeops_targetinvert PipeOpTargetInvert
Invert Target Transformations
mlr_pipeops_targetmutate PipeOpTargetMutate
Transform a Target by a Function
mlr_pipeops_targettrafoscalerange PipeOpTargetTrafoScaleRange
Linearly Transform a Numeric Target to Match Given Boundaries
mlr_pipeops_textvectorizer PipeOpTextVectorizer
Bag-of-word Representation of Character Features
mlr_pipeops_threshold PipeOpThreshold
Change the Threshold of a Classification Prediction
mlr_pipeops_tunethreshold PipeOpTuneThreshold
Tune the Threshold of a Classification Prediction
mlr_pipeops_unbranch PipeOpUnbranch
Unbranch Different Paths
mlr_pipeops_updatetarget PipeOpUpdateTarget
Transform a Target without an Explicit Inversion
mlr_pipeops_vtreat PipeOpVtreat
Interface to the vtreat Package
mlr_pipeops_yeojohnson PipeOpYeoJohnson
Yeo-Johnson Transformation of Numeric Features
PipeOp
PipeOp Base Class
PipeOpEnsemble
Ensembling Base Class
PipeOpImpute
Imputation Base Class
PipeOpTargetTrafo
Target Transformation Base Class
PipeOpTaskPreproc
Task Preprocessing Base Class
PipeOpTaskPreprocSimple
Simple Task Preprocessing Base Class

Pipelines

ppl() ppls()
Shorthand Graph Constructor
pipeline_bagging()
Create a bagging learner
pipeline_branch()
Branch Between Alternative Paths
pipeline_convert_types()
Convert Column Types
pipeline_greplicate()
Create Disjoint Graph Union of Copies of a Graph
pipeline_ovr()
Create A Graph to Perform "One vs. Rest" classification.
pipeline_robustify()
Robustify a learner
pipeline_stacking()
Create A Graph to Perform Stacking.
pipeline_targettrafo()
Transform and Re-Transform the Target Variable

Graphs

mlr_graphs
Dictionary of (sub-)graphs
pipeline_bagging()
Create a bagging learner
pipeline_branch()
Branch Between Alternative Paths
pipeline_convert_types()
Convert Column Types
pipeline_greplicate()
Create Disjoint Graph Union of Copies of a Graph
pipeline_ovr()
Create A Graph to Perform "One vs. Rest" classification.
pipeline_robustify()
Robustify a learner
pipeline_stacking()
Create A Graph to Perform Stacking.
pipeline_targettrafo()
Transform and Re-Transform the Target Variable
chain_graphs()
Chain a Series of Graphs

Learners

mlr_learners_graph GraphLearner
Encapsulate a Graph as a Learner
mlr_learners_classif.avg mlr_learners_regr.avg
Optimized Weighted Average of Features for Classification and Regression

Helpers

selector_all() selector_none() selector_type() selector_grep() selector_name() selector_invert() selector_intersect() selector_union() selector_setdiff() selector_missing() selector_cardinality_greater_than()
Selector Functions
as_graph()
Conversion to mlr3pipelines Graph
assert_graph()
Assertion for mlr3pipelines Graph
as_pipeop()
Conversion to mlr3pipelines PipeOp
assert_pipeop()
Assertion for mlr3pipelines PipeOp
is_noop()
Test for NO_OP
NO_OP
No-Op Sentinel Used for Alternative Branching
filter_noop()
Remove NO_OPs from a List
set_validate(<GraphLearner>)
Configure Validation for a GraphLearner
as.Multiplicity()
Convert an object to a Multiplicity
is.Multiplicity()
Check if an object is a Multiplicity

Abstract PipeOps

PipeOpEnsemble
Ensembling Base Class

PipeOp Type Inference

add_class_hierarchy_cache()
Add a Class Hierarchy to the Cache
reset_class_hierarchy_cache()
Reset the Class Hierarchy Cache
register_autoconvert_function()
Add Autoconvert Function to Conversion Register
reset_autoconvert_register()
Reset Autoconvert Register