规则替换 R 中的项目值

Question

所以，我正在尝试让规则与我的数据一起工作，我有 transaction_ID、Item_name 和 Item_ID。但是，如果我为 item_name 和 transaction_ID 调用先验函数，那就太慢了，但是如果我用 item_id 和 transaction_ID 调用它，那就真的很快了。那么，有没有办法用 item_id 创建规则，然后用 ids 代替它的真实姓名？这是一个代码示例：

library(arules)
library(arulesViz)

products <- c(1,1,1,3,4,5,6,4)
transaction_id <- c(2,2,3,3,3,4,4,4)
dataset <- data.frame(products ,transaction_id)
dataset
transaction <- as(split(dataset[,"products"],dataset[,"transaction_id"]), "transactions")

rule <- apriori(transaction, parameter = list(supp = 0.001, conf = 0.8))

inspect(rule)

products_id <- c(1,3,4,5,6)
names <- c("nail","Black Hammer 127","White desk 12","green desk","pink car")

cod <- data.frame(products = products_id, names)

Answer 1

最好的方法是使用函数 itemLabels:

替换交易中的项目标签

itemLabels(transaction)
  [1] "1" "3" "4" "5" "6"
itemLabels(transaction) <- c("nail","Black Hammer 127","White desk 12","green desk","pink car")
rule <- apriori(transaction, parameter = list(supp = 0.001, conf = 0.8))
inspect(rules)
      lhs                                 rhs                support   confidence
 [1]  {Black Hammer 127}               => {nail}             0.3333333 1 
 ...

split 相当慢。 ?transactions 中的示例说明了如何使用 split:

## Note: This is very slow for large datasets. It is much faster to 
## read transactions in this format from disk using read.transactions() 
## with format = "single".

规则替换 R 中的项目值

arules substitution of item values in R

transactions

r

rules

apriori

market-basket-analysis