Impute features by sampling from non-missing training data.
R6Class
object inheriting from PipeOpImpute
/PipeOp
.
PipeOpImputeSample$new(id = "imputesample", param_vals = list())
id
:: character(1)
Identifier of resulting object, default "imputesample"
.
param_vals
:: named list
List of hyperparameter settings, overwriting the hyperparameter settings that would otherwise be set during construction. Default list()
.
Input and output channels are inherited from PipeOpImputeSample
.
The output is the input Task
with all affected numeric features missing values imputed by values sampled (column-wise) from training data.
The $state
is a named list
with the $state
elements inherited from PipeOpImpute
.
The $state$model
is a named list
of training data with missings removed.
The parameters are the parameters inherited from PipeOpImpute
.
Uses the sample()
function. Features that are entirely NA
are imputed as the values given by vector()
of their type.
Only methods inherited from PipeOpImpute
/PipeOp
.
Other PipeOps: PipeOpEnsemble
,
PipeOpImpute
,
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_copy
,
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_imputehist
,
mlr_pipeops_imputemean
,
mlr_pipeops_imputemedian
,
mlr_pipeops_imputenewlvl
,
mlr_pipeops_kernelpca
,
mlr_pipeops_learner
,
mlr_pipeops_missind
,
mlr_pipeops_modelmatrix
,
mlr_pipeops_mutate
,
mlr_pipeops_nop
,
mlr_pipeops_pca
,
mlr_pipeops_quantilebin
,
mlr_pipeops_regravg
,
mlr_pipeops_removeconstants
,
mlr_pipeops_scalemaxabs
,
mlr_pipeops_scalerange
,
mlr_pipeops_scale
,
mlr_pipeops_select
,
mlr_pipeops_smote
,
mlr_pipeops_spatialsign
,
mlr_pipeops_subsample
,
mlr_pipeops_unbranch
,
mlr_pipeops_yeojohnson
,
mlr_pipeops
Other Imputation PipeOps: PipeOpImpute
,
mlr_pipeops_imputehist
,
mlr_pipeops_imputemean
,
mlr_pipeops_imputemedian
,
mlr_pipeops_imputenewlvl
# NOT RUN {
library("mlr3")
task = tsk("pima")
task$missings()
po = po("imputesample")
new_task = po$train(list(task = task))[[1]]
new_task$missings()
# }
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