Impute numerical features by their mean.

`R6Class`

object inheriting from `PipeOpImpute`

/`PipeOp`

.

PipeOpImputeMean$new(id = "imputemean", param_vals = list())

`id`

::`character(1)`

Identifier of resulting object, default`"imputemean"`

.`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 `PipeOpImputeMean`

.

The output is the input `Task`

with all affected numeric features missing values imputed by (column-wise) mean.

The `$state`

is a named `list`

with the `$state`

elements inherited from `PipeOpImpute`

.

The `$state$model`

is a named `list`

of `numeric(1)`

indicating the mean of the respective feature.

The parameters are the parameters inherited from `PipeOpImpute`

.

Uses the `mean()`

function. Features that are entirely `NA`

are imputed as `0`

.

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_imputemedian`

,
`mlr_pipeops_imputenewlvl`

,
`mlr_pipeops_imputesample`

,
`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_imputemedian`

,
`mlr_pipeops_imputenewlvl`

,
`mlr_pipeops_imputesample`

#> diabetes age glucose insulin mass pedigree pregnant pressure #> 0 0 5 374 11 0 0 35 #> triceps #> 227#> diabetes age pedigree pregnant glucose insulin mass pressure #> 0 0 0 0 0 0 0 0 #> triceps #> 0po$state$model#> $age #> [1] 33.24089 #> #> $glucose #> [1] 121.6868 #> #> $insulin #> [1] 155.5482 #> #> $mass #> [1] 32.45746 #> #> $pedigree #> [1] 0.4718763 #> #> $pregnant #> [1] 3.845052 #> #> $pressure #> [1] 72.40518 #> #> $triceps #> [1] 29.15342 #>