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我正在尝试使用 package.json 进行市场篮子分析arules。但是，我在使用apriori算法的时候，R报了如下信息。

dt <- split(deviceshowlist$prog_title, deviceshowlist$device_id)
dt2 <- as(dt,"transactions")
rules <- apriori(dt2, parameter = list(support = 0.01, confidence = 0.05, minlen=2))

先验的

参数规格：

print.default（参数）中的错误：尝试应用非功能

我查看了我的交易数据结构和 apriori 的功能。似乎没有什么不妥。请希望有人以前遇到过类似的问题并可以帮助我。

谢谢

我的dt和dt2的结构更新如下

 > str(dt)
    List of 5388
    $ 000000006201   : chr [1:2] "Modern Family" "Criminal Minds"
    $ 0000000080ed   : chr [1:5] "Blindspot" "Supergirl" "The Simpsons" "The Big Bang Theory" ...
    $ 000000009c7b   : chr [1:9] "Criminal Minds" "The Big Bang Theory" "Life in Pieces" "Limitless" ...
    $ 000000009e56   : chr [1:7] "Friends" "2 Broke Girls" "Best Time Ever With Neil Patrick Harris" "Blindspot" ...

> str(dt2)
Formal class 'transactions' [package "arules"] with 3 slots
  ..@ data       :Formal class 'ngCMatrix' [package "Matrix"] with 5 slots
  .. .. ..@ i       : int [1:25272] 10 21 5 21 27 30 35 0 8 10 ...
  .. .. ..@ p       : int [1:5389] 0 2 7 16 23 24 32 39 40 50 ...
  .. .. ..@ Dim     : int [1:2] 37 5388
  .. .. ..@ Dimnames:List of 2
  .. .. .. ..$ : NULL
  .. .. .. ..$ : NULL
  .. .. ..@ factors : list()
  ..@ itemInfo   :'data.frame': 37 obs. of  1 variable:
  .. ..$ labels: chr [1:37] "2 Broke Girls" "Agent X" "Ash vs Evil Dead" "Benders" ...
  ..@ itemsetInfo:'data.frame': 5388 obs. of  1 variable:
  .. ..$ transactionID: chr [1:5388] "000000006201" "0000000080ed" "000000009c7b" "000000009e56" ...


     device_id     prog_title
1 0000000080ed      Blindspot
2 0000000080ed      Supergirl
3 000000009c7b Life in Pieces
4 000000009c7b      Limitless
5 000000009c7b       Quantico
6 000000009c7b     Code Black
7 000000009c7b    The Muppets
8 000000009c7b      Supergirl
4

1 回答 1

0

确保您的 ID 列是一个因素：

library(arules)

deviceshowlist <- data.frame(device_id = c("0000000080ed","0000000080ed",rep("000000009c7b",6)),
                             prog_title = c("Blindspot","Supergirl","Life in Pieces","Limitless",
"Quantico","Code Black","The Muppets","Supergirl"), stringsAsFactors=F)

deviceshowlist$device_id <- as.factor(deviceshowlist$device_id)

str(deviceshowlist)
#'data.frame':  8 obs. of  2 variables:
#  $ device_id : Factor w/ 2 levels "0000000080ed",..: 1 1 2 2 2 2 2 2
#  $ prog_title: chr  "Blindspot" "Supergirl" "Life in Pieces" "Limitless" ...


dt <- split(deviceshowlist$prog_title, deviceshowlist$device_id)
dt2 <- as(dt,"transactions")
rules <- apriori(dt2, parameter = list(support = 0.01, confidence = 0.05, minlen=2))

# Apriori
# 
# Parameter specification:
#   confidence minval smax arem  aval originalSupport maxtime support minlen
# 0.05    0.1    1 none FALSE            TRUE       5    0.01      2
# maxlen target   ext
# 10  rules FALSE
# 
# Algorithmic control:
#   filter tree heap memopt load sort verbose
# 0.1 TRUE TRUE  FALSE TRUE    2    TRUE
# 
# Absolute minimum support count: 0
# 
# set item appearances ...[0 item(s)] done [0.00s].
# set transactions ...[7 item(s), 2 transaction(s)] done [0.00s].
# sorting and recoding items ... [7 item(s)] done [0.00s].
# creating transaction tree ... done [0.00s].
# checking subsets of size 1 2 3 4 5 6 done [0.00s].
# writing ... [188 rule(s)] done [0.00s].
# creating S4 object  ... done [0.00s].
于 2018-05-13T02:31:37.883 回答