Minimal joint mutual information maximisation filter calling praznik::JMIM() in package praznik.

This filter supports partial scoring (see Filter).

See also

Super class

mlr3filters::Filter -> FilterJMIM

Methods

Public methods

Inherited methods

Method new()

Create a FilterJMIM object.

Usage

FilterJMIM$new(
  id = "jmim",
  task_type = "classif",
  param_set = ParamSet$new(list(ParamInt$new("threads", lower = 0L, default = 0L))),
  packages = "praznik",
  feature_types = c("integer", "numeric", "factor", "ordered")
)

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

FilterJMIM$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

task = mlr3::tsk("iris") filter = flt("jmim") filter$calculate(task, nfeat = 2) as.data.table(filter)
#> feature score #> 1: Sepal.Length 1.0401337 #> 2: Petal.Width 0.9893676 #> 3: Sepal.Width NA #> 4: Petal.Length NA