目标:根据每个部门的报告生成前5个关联规则列表(按置信度)。
我现有的语法和测试数据:
# Create fake data; 1= used report, 0 = didn't use report
data <- data.frame(Dept=c('A','A','A','B','B','B'),
Rep1=c(1,1,1,1,1,1),
Rep2=c(0,0,0,1,1,1),
Rep3=c(1,1,1,0,0,0),
Rep4=c(0,1,0,1,1,0),
Rep5=c(0,0,0,0,0,0),
Rep6=c(1,1,0,0,1,0),
Rep7=c(1,1,1,1,1,0),
Rep8=c(0,0,0,1,1,0),
Rep9=c(1,0,0,1,1,0),
Rep10=c(1,1,0,0,1,1)
)
# Turn all variables to factors
data<-data.frame(lapply(data, factor))
# Changes 0s to NAs, only interested in rules where the report was used
data[data==0]<-NA
# lapply command to run apriori on the data when split by Dept
rules <- lapply(split(data, list(data$Dept)), function(x) {
# Turn split data into transactions
temp <- as(x[ , 2:length(x)], "transactions")
# Create rules; artificially low parameters for testing
temp <- apriori(temp, parameter = list(support=0.01, confidence=0.1, minlen=2, maxlen=2))
# Order rules by confidence, eventually will select top 5 (I'm able to do that), and change it to a data frame for later use
temp <- as(sort(temp, by = "confidence")[0:length(temp)], "data.frame")
})
# Breaks out the results into separate data.frames
list2env(rules,.GlobalEnv)
这导致每个部门约50条规则。但是,他们处于全球一级的部门。例如,Dept A data.frame有......
rules support confidence lift
{Rep9=1}=>{Rep6=1} .3333333 1.00000000 1.5
{Rep4=1}=>{Rep6=1} .3333333 1.00000000 1.5
...
理想情况下,我的data.frames应该看起来像......
系。 A仅报告9 data.frame
rules support confidence lift
{Rep9=1}=>{Rep6=1} .3333333 1.00000000 1.5
{Rep9=1}=>{Rep10=1} .3333333 1.00000000 1.5
...
系。 A仅报告4 data.frame
rules support confidence lift
{Rep4=1}=>{Rep6=1} .3333333 1.00000000 1.5
{Rep4=1}=>{Rep10=1} .3333333 1.00000000 1.5
...
答案 0 :(得分:0)
您需要查看规则模板,以将规则的左侧(LHS)限制到某个部门。请查看arules中if(next->pid != my_worker_pid)
schedule_work(next);
中的示例。
将LHS限制在某个部门的代码看起来有点像这样:
? APappearance