relief: RReliefF filter

In FSelectorRcpp: 'Rcpp' Implementation of 'FSelector' Entropy-Based Feature Selection Algorithms with a Sparse Matrix Support

RReliefF filter

Description

The algorithm finds weights of continuous and discrete attributes basing on a distance between instances.

Usage

relief(formula, data, x, y, neighboursCount = 5, sampleSize = 10)

Arguments

formula	An object of class formula with model description.
data	A data.frame accompanying formula.
x	A data.frame with attributes.
y	A vector with response variable.
neighboursCount	number of neighbours to find for every sampled instance
sampleSize	number of instances to sample

Details

The function and it's manual page taken directly from FSelector: Piotr Romanski and Lars Kotthoff (2018). FSelector: Selecting Attributes. R package version 0.31. https://CRAN.R-project.org/package=FSelector

Value

a data.frame containing the worth of attributes in the first column and their names as row names

References

Igor Kononenko: Estimating Attributes: Analysis and Extensions of RELIEF. In: European Conference on Machine Learning, 171-182, 1994.

Marko Robnik-Sikonja, Igor Kononenko: An adaptation of Relief for attribute estimation in regression. In: Fourteenth International Conference on Machine Learning, 296-304, 1997.

Examples

data(iris)

weights <- relief(Species~., iris, neighboursCount = 5, sampleSize = 20)
print(weights)
subset <- cut_attrs(weights, 2)
f <- to_formula(subset, "Species")
print(f)

FSelectorRcpp documentation built on April 28, 2023, 5:07 p.m.