View source: R/search.exhaustive.R
exhaustive.search | R Documentation |
The algorithm for searching atrribute subset space.
exhaustive.search(attributes, eval.fun)
attributes |
a character vector of all attributes to search in |
eval.fun |
a function taking as first parameter a character vector of all attributes and returning a numeric indicating how important a given subset is |
The algorithm searches the whole attribute subset space in breadth-first order.
A character vector of selected attributes.
Piotr Romanski
forward.search
, backward.search
, best.first.search
, hill.climbing.search
library(rpart)
data(iris)
evaluator <- function(subset) {
#k-fold cross validation
k <- 5
splits <- runif(nrow(iris))
results = sapply(1:k, function(i) {
test.idx <- (splits >= (i - 1) / k) & (splits < i / k)
train.idx <- !test.idx
test <- iris[test.idx, , drop=FALSE]
train <- iris[train.idx, , drop=FALSE]
tree <- rpart(as.simple.formula(subset, "Species"), train)
error.rate = sum(test$Species != predict(tree, test, type="c")) / nrow(test)
return(1 - error.rate)
})
print(subset)
print(mean(results))
return(mean(results))
}
subset <- exhaustive.search(names(iris)[-5], evaluator)
f <- as.simple.formula(subset, "Species")
print(f)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.