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### Consistency
# classification and regression
# continous and discrete data
consistency <- function(formula, data) {
# uses parent.env
evaluator <- function(attrs) {
attr_data = new_data[, attrs, drop=FALSE]
#deprecated
#attr_data = as.data.frame(lapply(attr_data, function(vec) { addNA(vec, ifany=TRUE) }))
#result = aggregate(new_data[[1]], as.list(attr_data), function(classes) {
hashvec = as.factor(apply(attr_data, 1, digest))
result = aggregate(new_data[[1]], list(hash=hashvec), function(classes) {
return(max(as.vector(table(classes))))
})
result = sum(result[[dim(result)[2]]]) / dim(attr_data)[1]
return(result)
}
new_data = get.data.frame.from.formula(formula, data)
new_data = discretize.all(formula, new_data)
column_names = names(new_data)
result = best.first.search(column_names[-1], evaluator)
return(result)
}
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