mlr_pipeops_scalerange

0th

Percentile

PipeOpScaleRange

Linearly transforms numeric data columns so they are between lower and upper. The formula for this is \(x' = a + x * b\), where \(b\) is \((upper - lower) / (max(x) - min(x))\) and \(a\) is \(-min(x) * b + lower\).

Keywords
datasets
Format

R6Class object inheriting from PipeOpTaskPreprocSimple/PipeOpTaskPreproc/PipeOp.

Construction

PipeOpScaleRange$new(id = "scalerange", param_vals = list())
  • id :: character(1) Identifier of resulting object, default "scalerange".

  • 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 PipeOpTaskPreproc.

The output is the input Task with scaled numeric features.

State

The $state is a named list with the $state elements inherited from PipeOpTaskPreproc, as well as the two transformation parameters \(a\) and \(b\) for each numeric feature.

Parameters

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

  • lower :: numeric(1) Target value of smallest item of input data. Default is 0.

  • upper :: numeric(1) Target value of greatest item of input data. Default is 1.

Methods

Only methods inherited from PipeOpTaskPreprocSimple/PipeOpTaskPreproc/PipeOp.

See Also

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_imputemean, 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_scale, mlr_pipeops_select, mlr_pipeops_smote, mlr_pipeops_spatialsign, mlr_pipeops_subsample, mlr_pipeops_unbranch, mlr_pipeops_yeojohnson, mlr_pipeops

Aliases
  • mlr_pipeops_scalerange
  • PipeOpScaleRange
Examples
# NOT RUN {
library("mlr3")

task = tsk("iris")
pop = po("scalerange", param_vals = list(lower = -1, upper = 1))

task$data()
pop$train(list(task))[[1]]$data()

pop$state
# }
Documentation reproduced from package mlr3pipelines, version 0.1.1, License: LGPL-3

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