mlr_pipeops_info: Customizable Information Printer

In mlr3pipelines: Preprocessing Operators and Pipelines for 'mlr3'

Customizable Information Printer

Description

PipeOpInfo prints its input to the console or a logger in a customizable way. Users can define how specific object classes should be displayed using custom printer functions.

Format

R6Class object inheriting from PipeOp

Construction

PipeOpInfo$new(id = "info", collect_multiplicity = FALSE, log_target = "lgr::mlr3/mlr3pipelines::info")

• id :: character(1)
  Identifier of resulting object, default "info"

• printer :: list
  Optional mapping from object classes to printer functions. Custom functions override default printer-functions.

• collect_multiplicity :: logical(1)
  If TRUE, the input is a Multiplicity collecting channel. Multiplicity input/output is accepted and the members are aggregated.

• log_target :: character(1)
  Specifies how the input object is printed to the console. By default it is directed to a logger, whose address can be customized using the form ⁠<output>::<argument1>::<argument2>⁠. Otherwise it can be printed as "message", "warning" or "cat". When set to "none", no customized information about the object will be printed.

Input and Output Channels

PipeOpInfo has one input channel called "input", it can take any type of input (*). PipeOpInfo has one output channel called "output", it can take any type of output (*).

State

The ⁠$state⁠ is left empty (list()).

Internals

PipeOpInfo forwards its input unchanged, but prints information about it depending on the printer and log_target settings.

Fields

Fields inherited from PipeOp, as well as:

• printer :: list
  Mapping of object classes to printer functions. Includes printer-specifications for Task, Prediction, NULL. Otherwise object is printed as is.

• log_target :: character(1)
  Specifies current output target.

Methods

Only methods inherited from PipeOp.

See Also

https://mlr-org.com/pipeops.html

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_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_imputemedian, mlr_pipeops_imputemode, mlr_pipeops_imputeoor, mlr_pipeops_imputesample, mlr_pipeops_isomap, mlr_pipeops_kernelpca, mlr_pipeops_learner, mlr_pipeops_learner_pi_cvplus, mlr_pipeops_learner_quantiles, 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_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

Examples

library("mlr3")

poinfo = po("info")
poinfo$train(list(tsk("mtcars")))
poinfo$predict(list(tsk("mtcars")))

# Specify customized console output for Task-objects
poinfo = po("info", log_target = "cat",
  printer = list(Task = function(x) list(head_data = head(x$data()), nrow = nrow(x$data())))
)

poinfo$train(list(tsk("iris")))
poinfo$predict(list(tsk("iris")))

mlr3pipelines documentation built on Nov. 7, 2025, 9:06 a.m.