The permutation filter randomly permutes the values of a single feature in a mlr3::Task to break the association with the response. The permutated feature, together with the unmodified features, is used to perform a mlr3::resample(). The permutation filter score is the difference between the aggregated performance of the mlr3::Measure and the performance estimated on the unmodified mlr3::Task.

Parameters

standardize

logical(1)
Standardize feature importance by maximum score.

nmc

integer(1)

Number of Monte-Carlo iterations to use in computing the feature importance.

See also

Super class

mlr3filters::Filter -> FilterPermutation

Public fields

learner

(mlr3::Learner)

resampling

(mlr3::Resampling)

measure

(mlr3::Measure)

Methods

Public methods

Inherited methods

Method new()

Create a FilterPermutation object.

Usage

FilterPermutation$new(
  learner = mlr3::lrn("classif.rpart"),
  resampling = mlr3::rsmp("holdout"),
  measure = NULL
)

Arguments

learner

(mlr3::Learner)
mlr3::Learner to use for model fitting.

resampling

(mlr3::Resampling)
mlr3::Resampling to be used within resampling.

measure

(mlr3::Measure)
mlr3::Measure to be used for evaluating the performance.


Method clone()

The objects of this class are cloneable with this method.

Usage

FilterPermutation$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.