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The data consist of 4601 email items, of which 1813 items were identified as spam.
spam7
This data frame contains the following columns:
total length of words in capitals
number of occurrences of the \$ symbol
number of occurrences of the ! symbol
number of occurrences of the word `money'
number of occurrences of the string `000'
number of occurrences of the word `make'
outcome variable, a factor with levels n not spam, y spam
n
y
# NOT RUN { require(rpart) spam.rpart <- rpart(formula = yesno ~ crl.tot + dollar + bang + money + n000 + make, data=spam7) plot(spam.rpart) text(spam.rpart) # }
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