R语言学习之关联规则算法

 library(arules)  #加载arules程序包
data(Groceries)  #调用数据文件
frequentsets=eclat(Groceries,parameter=list(support=0.05,maxlen=10))  #求频繁项集
inspect(frequentsets[1:10])    #察看求得的频繁项集
inspect(sort(frequentsets,by="support")[1:10])    #根据支持度对求得的频繁项集排序并察看（等价于inspect(sort(frequentsets)[1:10]）
rules=apriori(Groceries,parameter=list(support=0.01,confidence=0.01))    #求关联规则
summary(rules)    #察看求得的关联规则之摘要
x=subset(rules,subset=rhs%in%"whole milk"&lift>=1.2)    #求所需要的关联规则子集

inspect(sort(x,by="support")[1:5])    #根据支持度对求得的关联规则子集排序并察看

  lhs                   rhs             support confidence     lift
1 {other vegetables} => {whole milk} 0.07483477  0.3867578 1.513634
2 {rolls/buns}       => {whole milk} 0.05663447  0.3079049 1.205032
3 {yogurt}           => {whole milk} 0.05602440  0.4016035 1.571735
4 {root vegetables}  => {whole milk} 0.04890696  0.4486940 1.756031
5 {tropical fruit}   => {whole milk} 0.04229792  0.4031008 1.577595
>