Impute Numeric, Integer, POSIXct or Date Features by their Median

Impute numerical, integer, POSIXct or Date features by their median.

Format

R6Class object inheriting from PipeOpImpute/PipeOp.

Construction

PipeOpImputeMedian$new(id = "imputemedian", param_vals = list())

id :: character(1)
Identifier of resulting object, default "imputemedian".
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

Input and output channels are inherited from PipeOpImpute.

The output is the input Task with all affected numeric, integer, POSIXct and Date features missing values imputed by (column-wise) median.

State

The $state is a named list with the $state elements inherited from PipeOpImpute.

The $state$model is a named list of numeric(1), integer(1), POSIXct(1) or Date(1) indicating the median of the respective feature.

Parameters

The parameters are the parameters inherited from PipeOpImpute.

Internals

Uses the stats::median() function. Features that are entirely NA are imputed as 0.

Fields

Only fields inherited from PipeOp.

Methods

Only methods inherited from PipeOpImpute/PipeOp.

Other PipeOps: PipeOp, PipeOpEncodePL, PipeOpEnsemble, PipeOpImpute, PipeOpTargetTrafo, PipeOpTaskPreproc, PipeOpTaskPreprocSimple, mlr_pipeops, 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_classweightsex, 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_encodeplquantiles, mlr_pipeops_encodepltree, 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_imputemode, mlr_pipeops_imputeoor, mlr_pipeops_imputesample, mlr_pipeops_info, mlr_pipeops_isomap, mlr_pipeops_kernelpca, mlr_pipeops_learner, mlr_pipeops_learner_pi_cvplus, mlr_pipeops_learner_quantiles, mlr_pipeops_materialize, 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_splines, 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 Imputation PipeOps: PipeOpImpute, mlr_pipeops_imputeconstant, mlr_pipeops_imputehist, mlr_pipeops_imputelearner, mlr_pipeops_imputemean, mlr_pipeops_imputemode, mlr_pipeops_imputeoor, mlr_pipeops_imputesample

Examples

library("mlr3")

task = tsk("pima")
#> Warning: data set ‘PimaIndiansDiabetes2’ not found
#> Error in UseMethod("as_data_backend"): no applicable method for 'as_data_backend' applied to an object of class "NULL"
task$missings()
#> Error: object 'task' not found

po = po("imputemedian")
new_task = po$train(list(task = task))[[1]]
#> Error: object 'task' not found
new_task$missings()
#> Error: object 'new_task' not found

po$state$model
#> NULL