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The algorithm finds weights of discrete attributes basing on a chi-squared test.
chi.squared(formula, data)
a data.frame containing the worth of attributes in the first column and their names as row names
a symbolic description of a model
Piotr Romanski
The result is equal to Cramer's V coefficient between source attributes and destination attribute.
library(mlbench) data(HouseVotes84) weights <- chi.squared(Class~., HouseVotes84) print(weights) subset <- cutoff.k(weights, 5) f <- as.simple.formula(subset, "Class") print(f)
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