I need the codes please

. The file spam.txt contains 4601 email items, of which 1813 items were iden- tified as spam. The dataset contains the following columns: . crl.tot total length of words in capitals dollar number of occurrences of the $ symbol bang number of occurrences of the ! symbol money number of occurrences of the word "money" n000 number of occurrences of the string "000" make number of occurrences of the word "make" yesno a factor with levels n (not spam) and y (spam) Use the spam.txt dataset to build a discriminant rule to allocate future emails to either spam or not spam. Discuss the suitability of your rule. . The file spam.txt contains 4601 email items, of which 1813 items were iden- tified as spam. The dataset contains the following columns: . crl.tot total length of words in capitals dollar number of occurrences of the $ symbol bang number of occurrences of the ! symbol money number of occurrences of the word "money" n000 number of occurrences of the string "000" make number of occurrences of the word "make" yesno a factor with levels n (not spam) and y (spam) Use the spam.txt dataset to build a discriminant rule to allocate future emails to either spam or not spam. Discuss the suitability of your rule