Filter features by thresholding filter values.

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

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.