mlr_pipeops_collapsefactors: Collapse Factors

Description Format Construction Input and Output Channels State Parameters Internals Methods See Also Examples

Description

Collapses factors of type factor, ordered: Collapses the rarest factors in the training samples, until target_level_count levels remain. Levels that have prevalence above no_collapse_above_prevalence are retained, however. For factor variables, these are collapsed to the next larger level, for ordered variables, rare variables are collapsed to the neighbouring class, whichever has fewer samples.

Levels not seen during training are not touched during prediction; Therefore it is useful to combine this with the PipeOpFixFactors.

Format

R6Class object inheriting from PipeOpTaskPreprocSimple/PipeOpTaskPreproc/PipeOp.

Construction

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PipeOpCollapseFactors$new(id = "collapsefactors", param_vals = list())

Input and Output Channels

Input and output channels are inherited from PipeOpTaskPreproc.

The output is the input Task with rare affected factor and ordered feature levels collapsed.

State

The $state is a named list with the $state elements inherited from PipeOpTaskPreproc, as well as:

Parameters

The parameters are the parameters inherited from PipeOpTaskPreproc, as well as:

Internals

Makes use of the fact that levels(fact_var) = list(target1 = c("source1", "source2"), target2 = "source2") causes renaming of level "source1" and "source2" both to "target1", and also "source2" to "target2".

Methods

Only methods inherited from PipeOpTaskPreprocSimple/PipeOpTaskPreproc/PipeOp.

See Also

https://mlr3book.mlr-org.com/list-pipeops.html

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_colroles, 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

Examples

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library("mlr3")

mlr3pipelines documentation built on March 6, 2021, 1:06 a.m.