A simple Dictionary storing objects of class PipeOp.
Each PipeOp has an associated help page, see mlr_pipeops_[id].
Format
R6Class object inheriting from mlr3misc::Dictionary.
Fields
Fields inherited from Dictionary, as well as:
metainf::environment
Environment that stores themetainfargument of the$add()method. Only for internal use.
Methods
Methods inherited from Dictionary, as well as:
add(key, value, metainf = NULL)
(character(1),R6ClassGenerator,NULL|list)
Adds constructorvalueto the dictionary with keykey, potentially overwriting a previously stored item. Ifmetainfis notNULL(the default), it must be alistof arguments that will be given to thevalueconstructor (i.e.value$new()) when it needs to be constructed foras.data.tablePipeOplisting.
S3 methods
as.data.table(dict)Dictionary->data.table::data.table
Returns adata.tablewith columnskey(character),packages(character),input.num(integer),output.num(integer),input.type.train(character),input.type.predict(character),output.type.train(character),output.type.predict(character).
See also
Other mlr3pipelines backend related:
Graph,
PipeOp,
PipeOpTargetTrafo,
PipeOpTaskPreproc,
PipeOpTaskPreprocSimple,
mlr_graphs,
mlr_pipeops_updatetarget
Other PipeOps:
PipeOp,
PipeOpEnsemble,
PipeOpImpute,
PipeOpTargetTrafo,
PipeOpTaskPreproc,
PipeOpTaskPreprocSimple,
mlr_pipeops_adas,
mlr_pipeops_blsmote,
mlr_pipeops_boxcox,
mlr_pipeops_branch,
mlr_pipeops_chunk,
mlr_pipeops_classbalancing,
mlr_pipeops_classifavg,
mlr_pipeops_classweights,
mlr_pipeops_colapply,
mlr_pipeops_collapsefactors,
mlr_pipeops_colroles,
mlr_pipeops_copy,
mlr_pipeops_datefeatures,
mlr_pipeops_decode,
mlr_pipeops_encode,
mlr_pipeops_encodeimpact,
mlr_pipeops_encodelmer,
mlr_pipeops_featureunion,
mlr_pipeops_filter,
mlr_pipeops_fixfactors,
mlr_pipeops_histbin,
mlr_pipeops_ica,
mlr_pipeops_imputeconstant,
mlr_pipeops_imputehist,
mlr_pipeops_imputelearner,
mlr_pipeops_imputemean,
mlr_pipeops_imputemedian,
mlr_pipeops_imputemode,
mlr_pipeops_imputeoor,
mlr_pipeops_imputesample,
mlr_pipeops_kernelpca,
mlr_pipeops_learner,
mlr_pipeops_learner_pi_cvplus,
mlr_pipeops_learner_quantiles,
mlr_pipeops_missind,
mlr_pipeops_modelmatrix,
mlr_pipeops_multiplicityexply,
mlr_pipeops_multiplicityimply,
mlr_pipeops_mutate,
mlr_pipeops_nearmiss,
mlr_pipeops_nmf,
mlr_pipeops_nop,
mlr_pipeops_ovrsplit,
mlr_pipeops_ovrunite,
mlr_pipeops_pca,
mlr_pipeops_proxy,
mlr_pipeops_quantilebin,
mlr_pipeops_randomprojection,
mlr_pipeops_randomresponse,
mlr_pipeops_regravg,
mlr_pipeops_removeconstants,
mlr_pipeops_renamecolumns,
mlr_pipeops_replicate,
mlr_pipeops_rowapply,
mlr_pipeops_scale,
mlr_pipeops_scalemaxabs,
mlr_pipeops_scalerange,
mlr_pipeops_select,
mlr_pipeops_smote,
mlr_pipeops_smotenc,
mlr_pipeops_spatialsign,
mlr_pipeops_subsample,
mlr_pipeops_targetinvert,
mlr_pipeops_targetmutate,
mlr_pipeops_targettrafoscalerange,
mlr_pipeops_textvectorizer,
mlr_pipeops_threshold,
mlr_pipeops_tomek,
mlr_pipeops_tunethreshold,
mlr_pipeops_unbranch,
mlr_pipeops_updatetarget,
mlr_pipeops_vtreat,
mlr_pipeops_yeojohnson
Other Dictionaries:
mlr_graphs
Examples
library("mlr3")
mlr_pipeops$get("learner", lrn("classif.rpart"))
#> PipeOp: <classif.rpart> (not trained)
#> values: <xval=0>
#> Input channels <name [train type, predict type]>:
#> input [TaskClassif,TaskClassif]
#> Output channels <name [train type, predict type]>:
#> output [NULL,PredictionClassif]
# equivalent:
po("learner", learner = lrn("classif.rpart"))
#> PipeOp: <classif.rpart> (not trained)
#> values: <xval=0>
#> Input channels <name [train type, predict type]>:
#> input [TaskClassif,TaskClassif]
#> Output channels <name [train type, predict type]>:
#> output [NULL,PredictionClassif]
# all PipeOps currently in the dictionary:
as.data.table(mlr_pipeops)[, c("key", "input.num", "output.num", "packages")]
#> Key: <key>
#> key input.num output.num packages
#> <char> <int> <int> <list>
#> 1: adas 1 1 mlr3pipelines,smotefamily
#> 2: blsmote 1 1 mlr3pipelines,smotefamily
#> 3: boxcox 1 1 mlr3pipelines,bestNormalize
#> 4: branch 1 NA mlr3pipelines
#> 5: chunk 1 NA mlr3pipelines
#> 6: classbalancing 1 1 mlr3pipelines
#> 7: classifavg NA 1 mlr3pipelines,stats
#> 8: classweights 1 1 mlr3pipelines
#> 9: colapply 1 1 mlr3pipelines
#> 10: collapsefactors 1 1 mlr3pipelines
#> 11: colroles 1 1 mlr3pipelines
#> 12: copy 1 NA mlr3pipelines
#> 13: datefeatures 1 1 mlr3pipelines
#> 14: decode 1 1 mlr3pipelines
#> 15: encode 1 1 mlr3pipelines,stats
#> 16: encodeimpact 1 1 mlr3pipelines
#> 17: encodelmer 1 1 mlr3pipelines,lme4,nloptr
#> 18: featureunion NA 1 mlr3pipelines
#> 19: filter 1 1 mlr3pipelines
#> 20: fixfactors 1 1 mlr3pipelines
#> 21: histbin 1 1 mlr3pipelines,graphics
#> 22: ica 1 1 mlr3pipelines,fastICA
#> 23: imputeconstant 1 1 mlr3pipelines
#> 24: imputehist 1 1 mlr3pipelines,graphics
#> 25: imputelearner 1 1 mlr3pipelines
#> 26: imputemean 1 1 mlr3pipelines
#> 27: imputemedian 1 1 mlr3pipelines,stats
#> 28: imputemode 1 1 mlr3pipelines
#> 29: imputeoor 1 1 mlr3pipelines
#> 30: imputesample 1 1 mlr3pipelines
#> 31: kernelpca 1 1 mlr3pipelines,kernlab
#> 32: learner 1 1 mlr3pipelines
#> 33: learner_cv 1 1 mlr3pipelines
#> 34: learner_pi_cvplus 1 1 mlr3pipelines
#> 35: learner_quantiles 1 1 mlr3pipelines
#> 36: missind 1 1 mlr3pipelines
#> 37: modelmatrix 1 1 mlr3pipelines,stats
#> 38: multiplicityexply 1 NA mlr3pipelines
#> 39: multiplicityimply NA 1 mlr3pipelines
#> 40: mutate 1 1 mlr3pipelines
#> 41: nearmiss 1 1 mlr3pipelines,themis
#> 42: nmf 1 1 mlr3pipelines,MASS,NMF
#> 43: nop 1 1 mlr3pipelines
#> 44: ovrsplit 1 1 mlr3pipelines
#> 45: ovrunite 1 1 mlr3pipelines
#> 46: pca 1 1 mlr3pipelines
#> 47: proxy NA 1 mlr3pipelines
#> 48: quantilebin 1 1 mlr3pipelines,stats
#> 49: randomprojection 1 1 mlr3pipelines
#> 50: randomresponse 1 1 mlr3pipelines
#> 51: regravg NA 1 mlr3pipelines
#> 52: removeconstants 1 1 mlr3pipelines
#> 53: renamecolumns 1 1 mlr3pipelines
#> 54: replicate 1 1 mlr3pipelines
#> 55: rowapply 1 1 mlr3pipelines
#> 56: scale 1 1 mlr3pipelines
#> 57: scalemaxabs 1 1 mlr3pipelines
#> 58: scalerange 1 1 mlr3pipelines
#> 59: select 1 1 mlr3pipelines
#> 60: smote 1 1 mlr3pipelines,smotefamily
#> 61: smotenc 1 1 mlr3pipelines,themis
#> 62: spatialsign 1 1 mlr3pipelines
#> 63: subsample 1 1 mlr3pipelines
#> 64: targetinvert 2 1 mlr3pipelines
#> 65: targetmutate 1 2 mlr3pipelines
#> 66: targettrafoscalerange 1 2 mlr3pipelines
#> 67: textvectorizer 1 1 mlr3pipelines,quanteda,stopwords
#> 68: threshold 1 1 mlr3pipelines
#> 69: tomek 1 1 mlr3pipelines,themis
#> 70: tunethreshold 1 1 mlr3pipelines,bbotk
#> 71: unbranch NA 1 mlr3pipelines
#> 72: vtreat 1 1 mlr3pipelines,vtreat
#> 73: yeojohnson 1 1 mlr3pipelines,bestNormalize
#> key input.num output.num packages