Explicate a Multiplicity
by turning the input Multiplicity
into multiple outputs.
This PipeOp
has multiple output channels; the members of the input Multiplicity
are forwarded each along a single edge. Therefore, only multiplicities with exactly as many
members as outnum
are accepted.
Note that Multiplicity
is currently an experimental features and the implementation or UI
may change.
PipeOpMultiplicityExply$new(outnum , id = "multiplicityexply", param_vals = list())
outnum
:: numeric(1)
| character
Determines the number of output channels.
id
:: character(1)
Identifier of the resulting object, default "multiplicityexply"
.
param_vals
:: named list
List of hyperparameter settings, overwriting the hyperparameter settings that would otherwise
be set during construction. Default list()
.
PipeOpMultiplicityExply
has a single input channel named "input"
, collecting a
Multiplicity
of type any ("[*]"
) both during training and prediction.
PipeOpMultiplicityExply
has multiple output channels depending on the outnum
construction
argument, named "output1"
, "output2"
returning the elements of the unclassed input
Multiplicity
.
The $state
is left empty (list()
).
PipeOpMultiplicityExply
has no Parameters.
outnum
should match the number of elements of the unclassed input Multiplicity
.
Only fields inherited from PipeOp
.
Only methods inherited from PipeOp
.
Other PipeOps:
PipeOpEnsemble
,
PipeOpImpute
,
PipeOpTargetTrafo
,
PipeOpTaskPreprocSimple
,
PipeOpTaskPreproc
,
PipeOp
,
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_encodeimpact
,
mlr_pipeops_encodelmer
,
mlr_pipeops_encode
,
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_missind
,
mlr_pipeops_modelmatrix
,
mlr_pipeops_multiplicityimply
,
mlr_pipeops_mutate
,
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_scalemaxabs
,
mlr_pipeops_scalerange
,
mlr_pipeops_scale
,
mlr_pipeops_select
,
mlr_pipeops_smote
,
mlr_pipeops_spatialsign
,
mlr_pipeops_subsample
,
mlr_pipeops_targetinvert
,
mlr_pipeops_targetmutate
,
mlr_pipeops_targettrafoscalerange
,
mlr_pipeops_textvectorizer
,
mlr_pipeops_threshold
,
mlr_pipeops_tunethreshold
,
mlr_pipeops_unbranch
,
mlr_pipeops_updatetarget
,
mlr_pipeops_vtreat
,
mlr_pipeops_yeojohnson
,
mlr_pipeops
Other Multiplicity PipeOps:
Multiplicity()
,
PipeOpEnsemble
,
mlr_pipeops_classifavg
,
mlr_pipeops_featureunion
,
mlr_pipeops_multiplicityimply
,
mlr_pipeops_ovrsplit
,
mlr_pipeops_ovrunite
,
mlr_pipeops_regravg
,
mlr_pipeops_replicate
Other Experimental Features:
Multiplicity()
,
mlr_pipeops_multiplicityimply
,
mlr_pipeops_ovrsplit
,
mlr_pipeops_ovrunite
,
mlr_pipeops_replicate
# NOT RUN {
library("mlr3")
task1 = tsk("iris")
task2 = tsk("mtcars")
po = po("multiplicityexply", outnum = 2)
po$train(list(Multiplicity(task1, task2)))
po$predict(list(Multiplicity(task1, task2)))
# }
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