R语言学习_关联规则

关联规则
挖掘目的
发现商品之间的关系模式

指标
    支持度 support(x) = P(x)
    置信度 confidence(X -> Y) = support(X,Y)/support(X)
    提升度 lift(X -> Y) = confidence(X -> Y)/support(Y)
    关联规则 最小支持度阈值、最小置信度阈值

Apriori算法

R的函数
    arules包
        read.transactions
        apriori
        inspect

R语言实例：
# install.packages(‘arules’)
> library(arules)
> gd = read.transactions(‘e:/groceries.csv’,sep = ‘,’)
> # data(“Groceries”)
> # inspect(Groceries)

> summary(gd)
> inspect(gd)
> inspect(gd[1:5])

> itemFrequency(gd)
> itemFrequencyPlot(gd,support = 0.1)     # 支持度
> itemFrequencyPlot(gd,topN = 30)         # top N

> myrules = apriori(data = gd,parameter = list(support = 0.01,confidence = 0.3,minlen = 1))
> inspect(myrules)
> inspect(sort(myrules,by = 'lift'))

> summary(myrules)
> write(myrules,file = 'e:/grules.txt',sep = ',',col.names = NA)    # 把生成的结果写入文件