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mlr (version 2.13)

generateFilterValuesData: Calculates feature filter values.

Description

Calculates numerical filter values for features. For a list of features, use listFilterMethods.

Usage

generateFilterValuesData(task, method = "randomForestSRC.rfsrc",
  nselect = getTaskNFeats(task), ..., more.args = list())

Arguments

task

(Task) The task.

method

(character) Filter method(s), see above. Default is “randomForestSRC.rfsrc”.

nselect

(integer(1)) Number of scores to request. Scores are getting calculated for all features per default.

...

(any) Passed down to selected method. Can only be use if method contains one element.

more.args

(named list) Extra args passed down to filter methods. List elements are named with the filter method name the args should be passed down to. A more general and flexible option than .... Default is empty list.

Value

(FilterValues). A list containing:

task.desc

[TaskDesc) Task description.

data

(data.frame) with columns:

  • name(character) Name of feature.

  • type(character) Feature column type.

  • method(numeric) One column for each method with the feature importance values.

See Also

Other generate_plot_data: generateCalibrationData, generateCritDifferencesData, generateFeatureImportanceData, generateLearningCurveData, generatePartialDependenceData, generateThreshVsPerfData, getFilterValues, plotFilterValues

Other filter: filterFeatures, getFilterValues, getFilteredFeatures, listFilterMethods, makeFilterWrapper, makeFilter, plotFilterValues