
The algorithm finds weights of continous attributes basing on their correlation with continous class attribute.
linear.correlation(formula, data)
rank.correlation(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
data to process
Piotr Romanski
linear.correlation
uses Pearson's correlation
rank.correlation
uses Spearman's correlation
Rows with NA
values are not taken into consideration.
library(mlbench)
data(BostonHousing)
d=BostonHousing[-4] # only numeric variables
weights <- linear.correlation(medv~., d)
print(weights)
subset <- cutoff.k(weights, 3)
f <- as.simple.formula(subset, "medv")
print(f)
weights <- rank.correlation(medv~., d)
print(weights)
subset <- cutoff.k(weights, 3)
f <- as.simple.formula(subset, "medv")
print(f)
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