relief: RReliefF filter
In Najah-lshanableh/R-data-mining: Selecting Attributes

Description Usage Arguments Details Value Author(s) References Examples

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

1	relief(formula, data, neighbours.count = 5, sample.size = 10)

`formula`	a symbolic description of a model
`data`	data to process
`neighbours.count`	number of neighbours to find for every sampled instance
`sample.size`	number of instances to sample

The algorithm samples instances and finds their nearest hits and misses. Considering that result, it evaluates weights of attributes.

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

Piotr Romanski

-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.

  data(iris)
  
  weights <- relief(Species~., iris, neighbours.count = 5, sample.size = 20)
  print(weights)
  subset <- cutoff.k(weights, 2)
  f <- as.simple.formula(subset, "Species")
  print(f)