Changes the column roles of the input Task according to new_role.
R6Class object inheriting from PipeOpTaskPreprocSimple/PipeOpTaskPreproc/PipeOp.
PipeOpColRoles$new(id = "colroles", param_vals = list())
id :: character(1)
Identifier of resulting object, default "colroles".
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 PipeOpTaskPreproc.
The output is the input Task with transformed column roles according to new_role.
The $state is a named list with the $state elements inherited from PipeOpTaskPreproc.
The parameters are the parameters inherited from PipeOpTaskPreproc, as well as:
new_role :: list
Named list of new column roles. The names must match the column names of the input task that
will later be trained/predicted on. Each entry of the list must contain a character vector with
possible values of mlr_reflections$task_col_roles. If the value is
given as character(), the column will be dropped from the input task. Changing the role of a
column results in this column loosing its previous role(s). Setting a new target variable or
changing the role of an existing target variable is not supported.
Only methods inherited from PipeOpTaskPreprocSimple/PipeOpTaskPreproc/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_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_multiplicityexply,
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
# NOT RUN {
library("mlr3")
task = tsk("boston_housing")
pop = po("colroles", param_vals = list(
new_role = list(cmedv = "order")
))
pop$train(list(task))
# }
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