R: Calculates feature filter values.

generateFilterValuesData {mlr} | R Documentation

## 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.

[[TaskDesc]: R:[TaskDesc [data.frame]: R:data.frame [character]: R:character [character]: R:character [numeric]: R:numeric

### See Also

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

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

[Package mlr version 2.12.1 Index]