数据见附件

   name Num control power wisdom political charm loyalty coutry origin status

1   夏侯惇   1      94    96     62        56    78      99      1      1      1

2     许褚   2      83    97     26        16    68      89      1      1      1

3     荀攸   3      60    38     94        91    80      86      1      1      4

4     荀彧   4      64    35     97        90    84      80      1      1      4

5     张合   5      88    93     61        54    62      85      1      1      1

6     程昱   6      82    25     91        80    74      89      1      1      4

7     张辽   7      91    90     82        69    85      88      1      1      1

8     于禁   8      77    74     51        48    60      85      1      1      1

9     曹仁   9      79    83     61        58    68      95      1      1      1

10    曹洪  10      76    75     45        42    70      92      1      1      1

转换后的数据：kingdom3

items              transactionID

1   {name=夏侯惇,

     control=统帅,

     power=超级,

     wisdom=普通,

     political=普通,

     charm=喜欢,

     loyalty=死士}               1

2   {name=许褚,

     control=将军,

     power=超级,

     wisdom=弱智,

     political=普通,

     charm=普通,

     loyalty=死士}               2

函数具体使用见文档。

<br />
library(arules)<br />
<br />
# 转换数值类型数据<br />
 king[["power"]]<-ordered(cut(king[["power"]],c(0,60,80,95,110)),label=c("普通","强悍","高手","超级"))<br />
 king[["wisdom"]]<-ordered(cut(king[["wisdom"]],c(0,50,75,90,100)),label=c("弱智","普通","聪明","智慧"))<br />
 king[["control"]]<-ordered(cut(king[["control"]],c(0,50,75,90,100)),label=c("小兵","校尉","将军","统帅"))<br />
 king[["political"]]<-ordered(cut(king[["political"]],c(0,60,78,90,105)),label=c("普通","战术家","政治家","战略家"))<br />
 king[["charm"]]<-ordered(cut(king[["charm"]],c(0,55,75,90,100)),label=c("讨厌","普通","喜欢","吸引"))<br />
 king[["loyalty"]]<-ordered(cut(king[["loyalty"]],c(-1,55,71,85,101)),label=c("奸贼","普通","忠臣","死士"))<br />
<br />
kingdom<-data.frame(name=king[,1],king[,3:8])<br />
<br />
#转换为transactions结构<br />
kingdom3<- as(kingdom, "transactions")<br />
 <br />
itemFrequencyPlot(kingdom3, support = 0.5, cex.names = 0.8)<br />
<br />
image(kingdom3)<br />
itemFrequency(kingdom3, type = "relative")<br />
itemFrequency(kingdom3, type = "absolute")<br />
#分别用apriori、eclat函数<br />
rules <- apriori(kingdom3, parameter = list(support = 0.01,confidence = 0.6))<br />
fsets <- eclat(kingdom3, parameter = list(support = 0.05), control = list(verbose = FALSE))<br />
<br />
summary(rules)<br />
summary(fsets)<br />
<br />
rulesControl <- subset(rules, subset = rhs %in% "control=统帅" & lift > 1.2)<br />
rulesWisdom  <- subset(rules, subset = rhs %in% "wisdom=智慧" &lift > 2.2)<br />
inspect(rulesControl)<br />
inspect(rulesWisdom)<br />
inspect(head(SORT(rulesControl, by = "confidence"), n = 3))<br />
<br />
singleItems <- fsets[size(items(fsets)) == 4]<br />
inspect(singleItems)<br />
<br />
<br />
WRITE(rulesControl, file = "data.csv", sep = ",", col.names = NA)<br />
<br />
<br />