Question

我正在尝试使用ar中的arules包中的apriori函数找到关联规则。

rules <- apriori(data=data, parameter=list(supp=0.001,conf = 0.08), 
                  appearance = list(default="lhs",rhs="YOGHURT"),
                  control = list(verbose=F))

rules <- sort(rules, decreasing=TRUE,by="confidence")

inspect(rules[1:3])


    lhs       rhs      support      confidence       lift
1. {A,B}     {C}       0.04           0.96           0.25
2. {C,A}     {D}       0.05           0.95           0.26
3. {B,D}     {A,C}     0.03           0.93           0.24

通过上面显示的代码，我得到了一些保存在变量“规则”中的关联规则，这些规则以减少的方式排列。但我想通过信心和电梯同时订购这些规则。我尝试了这个但是我收到了一个错误：

rules <- sort(rules, decreasing=TRUE,by=c("confidence","lift"))

Error in .subset2(x, i, exact = exact) : subscript out of bounds

有没有办法按信心排序规则并同时提升？

Answer 1

我没想过这个。你可以复制＆amp;加载arules后，将以下代码粘贴到R会话中。

setMethod("sort", signature(x = "associations"),
  function (x, decreasing = TRUE, na.last = NA, by = "support", ...) {
    q <- quality(x)
    q <- q[, pmatch(by, colnames(q)), drop = FALSE]
    if(is.null(q)) stop("Unknown interest measure to sort by.")
    if(length(x) == 0) return(x)

    x[do.call(order, c(q, list(na.last = na.last, decreasing = decreasing)))]
})

现在您的原始代码应该可以使用。

> data("Adult")
> rules <- apriori(Adult, parameter = list(supp = 0.5, conf = 0.9, target = "rules"))
> inspect(head(sort(rules, by=c("supp", "conf"))))
  lhs                               rhs                   support confidence      lift
1 {}                             => {capital-loss=None} 0.9532779  0.9532779 1.0000000
2 {}                             => {capital-gain=None} 0.9173867  0.9173867 1.0000000
3 {capital-gain=None}            => {capital-loss=None} 0.8706646  0.9490705 0.9955863
4 {capital-loss=None}            => {capital-gain=None} 0.8706646  0.9133376 0.9955863
5 {native-country=United-States} => {capital-loss=None} 0.8548380  0.9525461 0.9992323
6 {native-country=United-States} => {capital-gain=None} 0.8219565  0.9159062 0.9983862

这将是下一个arules版本的一部分。

Answer 2

假设你有

library(arules)
data("Adult")
rules <- apriori(Adult, parameter = list(supp = 0.5, conf = 0.9, target = "rules"))

然后你可以尝试

df <- as(rules, "data.frame") 
df[order(df$lift, df$confidence), ]

通过提升和信心排序规则

2 个答案: