filterFeatures: Filter features by thresholding filter values.

In riebetob/mlr: Machine Learning in R

Description

First, calls generateFilterValuesData. Features are then selected via select and val.

Usage

filterFeatures(task, method = "randomForestSRC.rfsrc", fval = NULL,
  perc = NULL, abs = NULL, threshold = NULL, mandatory.feat = NULL, ...)

Arguments

task	[Task] The task.
method	[character(1)] See listFilterMethods. Default is “randomForestSRC.rfsrc”.
fval	[FilterValues] Result of generateFilterValuesData. If you pass this, the filter values in the object are used for feature filtering. method and ... are ignored then. Default is NULL and not used.
perc	[numeric(1)] If set, select perc*100 top scoring features. Mutually exclusive with arguments abs and threshold.
abs	[numeric(1)] If set, select abs top scoring features. Mutually exclusive with arguments perc and threshold.
threshold	[numeric(1)] If set, select features whose score exceeds threshold. Mutually exclusive with arguments perc and abs.
mandatory.feat	[character] Mandatory features which are always included regardless of their scores
...	[any] Passed down to selected filter method.

Value

[Task].

See Also

Other filter: generateFilterValuesData, getFilterValues, getFilteredFeatures, listFilterMethods, makeFilterWrapper, makeFilter, plotFilterValuesGGVIS, plotFilterValues

riebetob/mlr documentation built on May 20, 2019, 5:58 p.m.