R語言學習之關聯規則算法

 library(arules)  #加載arules程序包
data(Groceries)  #調用數據文件
frequentsets=eclat(Groceries,parameter=list(support=0.05,maxlen=10))  #求頻繁項集
inspect(frequentsets[1:10])    #察看求得的頻繁項集
inspect(sort(frequentsets,by="support")[1:10])    #根據支持度對求得的頻繁項集排序並察看（等價於inspect(sort(frequentsets)[1:10]）
rules=apriori(Groceries,parameter=list(support=0.01,confidence=0.01))    #求關聯規則
summary(rules)    #察看求得的關聯規則之摘要
x=subset(rules,subset=rhs%in%"whole milk"&lift>=1.2)    #求所須要的關聯規則子集

inspect(sort(x,by="support")[1:5])    #根據支持度對求得的關聯規則子集排序並察看

  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
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