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问题:
I'm working with some large transactions data. I've been using read.transactions and apriori (parts of the arules package) to mine for frequent item pairings.
My problem is this: when rules are generated (using "inspect()") I can easily view them in the R console. Right now I'm manually copying the results into a text file, then saving and opening in excel. I'd like to just save the generated rules using write.csv, or something similar, but when I try, I receive an error that the data cannot be coerced into data.frame.
Does anyone have experience doing this successfully in R?
回答1:
I know I'm answering my own question, but I found out that the solution is to use as() to convert the rules into a data frame. [I'm new to R, so I missed this my first time searching for a solution.] From there, it can easily be manipulated in any way you'd like (sub setting, sorting, exporting, etc.).
> mba = read.transactions(file="Book2.csv",rm.duplicates=FALSE, format="single", sep=",",cols=c(1,2)); > rules_1 <- apriori(mba,parameter = list(sup = 0.001, conf = 0.01, target="rules")); > as(rules_1, "data.frame");
回答2:
Another way to achieve that would be:
write(rules_1, file = "association_rules.csv", sep = ",", quote = TRUE, row.names = FALSE)