Variance filter calling stats::var().

Argument na.rm defaults to TRUE here.

See also

Super class

mlr3filters::Filter -> FilterVariance

Methods

Public methods

Inherited methods

Method new()

Create a FilterVariance object.

Usage

FilterVariance$new(
  id = "variance",
  task_type = c("classif", "regr"),
  param_set = ParamSet$new(list(ParamLgl$new("na.rm", default = TRUE))),
  packages = "stats",
  feature_types = c("integer", "numeric")
)

Arguments

id

(character(1))
Identifier for the filter.

task_type

(character())
Types of the task the filter can operator on. E.g., "classif" or "regr".

param_set

(paradox::ParamSet)
Set of hyperparameters.

packages

(character())
Set of required packages. Note that these packages will be loaded via requireNamespace(), and are not attached.

feature_types

(character())
Feature types the filter operates on. Must be a subset of mlr_reflections$task_feature_types.


Method clone()

The objects of this class are cloneable with this method.

Usage

FilterVariance$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

task = mlr3::tsk("mtcars") filter = flt("variance") filter$calculate(task) head(filter$scores, 3)
#> disp hp qsec #> 15360.799829 4700.866935 3.193166
#> feature score #> 1: disp 1.536080e+04 #> 2: hp 4.700867e+03 #> 3: qsec 3.193166e+00 #> 4: cyl 3.189516e+00 #> 5: carb 2.608871e+00 #> 6: wt 9.573790e-01 #> 7: gear 5.443548e-01 #> 8: drat 2.858814e-01 #> 9: vs 2.540323e-01 #> 10: am 2.489919e-01