mlr (version 2.10)

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 Name of feature.
• type Feature column type.
• A column for each method with the feature importance values.

See Also

Other generate_plot_data: generateCalibrationData, generateCritDifferencesData, generateFeatureImportanceData, generateFunctionalANOVAData, generateLearningCurveData, generatePartialDependenceData, generateThreshVsPerfData, getFilterValues, plotFilterValues Other filter: filterFeatures, getFilterValues, getFilteredFeatures, makeFilterWrapper, plotFilterValuesGGVIS, plotFilterValues