feature_selection_relief: Feature selection by RELIEF

In daltoolbox: Leveraging Experiment Lines to Data Analytics

Feature selection by RELIEF

Description

Rank and select features using a simplified RELIEF algorithm.

Usage

feature_selection_relief(
  attribute,
  features = NULL,
  top = NULL,
  cutoff = NULL,
  m = 50
)

Arguments

attribute	target attribute name
features	optional vector of feature names (default: all columns except attribute)
top	optional number of top features to keep
cutoff	optional minimum RELIEF weight to keep a feature
m	number of sampled instances for RELIEF updates

Details

For each sampled instance, the algorithm compares nearest hit/miss neighbors and updates feature weights.

Value

returns an object of class feature_selection_relief

Examples

data(iris)
fg <- feature_generation(
 IsVersicolor = ifelse(Species == "versicolor", "versicolor", "not_versicolor")
)
iris_bin <- transform(fg, iris)
iris_bin$IsVersicolor <- factor(iris_bin$IsVersicolor)
fs <- feature_selection_relief("IsVersicolor", top = 2, m = 50)
fs <- fit(fs, iris_bin)
fs$selected
transform(fs, iris_bin) |> names()

daltoolbox documentation built on May 14, 2026, 9:06 a.m.