将字符向量转换为 arules 的事务

Question

请帮助将购物商品的字符向量转换为 "transactions" 规则。原始数据是这样的：

shopping_items <- c("apple banana", "orange", "tea orange beef")

向量中的每个元素代表单笔交易中购买的物品，物品之间用space " "分隔，例如交易1包括两个物品，苹果和香蕉。我如何将其转换为 "transactions" 类型以便我可以在 arules 中使用它？

提前致谢！

Answer 1

实施可能不是最佳的，但您可以尝试改进它。

library(stringi)
library(arules)
library(purrr)

shopping_items <- c("apple banana", "orange", "tea orange beef")

str <- paste(shopping_items,collapse = ' ')

# unique items
str_un <- unique(unlist(stri_split_fixed(str,' ')))

# create a dataframe with dimensions:
# length(shopping_items) x length(str_un)
df <- as.data.frame(matrix(rep(0,length(str_un)*length(shopping_items )),ncol=length(str_un)))
names(df) <- str_un

# positions of 1's in each column
vecs <- map(str_un,grep,shopping_items)

sapply(1:length(str_un), function(x) df[,x][vecs[[x]]] <<- 1)
df[] <- lapply(df,as.factor)

# Generate a transactions dataset.
tr <- as(df, "transactions")

# Generate the association rules.
# rules <- apriori(tr, ...

Answer 2

这是简短的版本：

library(arules)
shopping_items <- c("apple banana", "orange", "tea orange beef")    

trans <- as(strsplit(shopping_items, " "), "transactions")

inspect(trans)
    items            
[1] {apple,banana}   
[2] {orange}         
[3] {beef,orange,tea}

将字符向量转换为 arules 的事务

convert character vector to transactions for arules

r

apriori

arules