View source: R/selector.relief.R
relief | R Documentation |
The algorithm finds weights of continous and discrete attributes basing on a distance between instances.
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)
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