I am trying to understand the use of R to run the apriori algorithm to mine association rules.Referencing an online exam question with solutions provided on Studocs Q2.2, it is expected that I get 8 association rules which fulfill the minimum support and minimum confidence criteria. However, I tried to run it in R and I only got 7, the missing rule being milk -> bread,butter.
May I know if anyone knows what I can do to allow the R snippet to produce the 8th rule or any rule that has an RHS length of more than 1.
Here is the snippet of R code which contains the transaction data as described in the question and the use of apriori. Let me know if more information is required to solve the problem.
library('arules')
library('arulesViz')
dataset = list(
c("Bread", "Butter", "Milk"),
c("Bread", "Butter"),
c("Beer", "Cookies", "Diapers"),
c("Milk", "Diapers", "Bread", "Butter"),
c("Beer", "Diapers")
)
Groceries = transactions(dataset)
itemsets <- apriori(Groceries,
parameter=list(
support=0.4, confidence = 0.7))
inspect(sort(itemsets, by = "support"))
