tr_dataf=data.frame(trID=c(rep(1,2),rep(2:5,each=4)),item=c("Bread", "Milk",
                                                            "Bread", "Diaper", "Beer", "Eggs",
                                                            "Milk","Diaper", "Beer", "Coke",
                                                            "Bread", "Milk","Diaper","Beer",
                                                            "Bread", "Milk", "Diaper","Coke"))
tr_dataf
trans4=as(split(tr_dataf[,"item"],tr_dataf[,"trID"]),"transactions")
trans4
inspect(trans4)

attributes(trans4)

itemFreq=itemFrequency(trans4)
orderItemFreq=sort(itemFreq,decreasing = T)

itemFrequencyPlot(trans4,topN=10,horiz=T,col="pink",border="lightblue",fg="deepskyblue3",col.axis="deepskyblue4",col.lab="deepskyblue4")

library(wordcloud2)

tabletr=table(tr_dataf$item)
tabletr=sort(tabletr,decreasing = T)

wordcloud2(tabletr,size=0.5,shape = "star")


####################################### generate association rules#####################
rules.tr=apriori(trans4,parameter = list(minlen=2,support=0.5,confidence=0.5),target="rules")
inspect(rules.tr)
inspect(head(rules.tr@lhs))


library(arulesViz)
plot(rules.tr) 

plot(rules.tr,method = "grouped") 


#####Extract rules of interest

rules.trs=sort(rules.tr,decreasing = T,by="lift")
inspect(rules.trs)
plot(rules.tr,method = "graph",lty=10)


####################################find redundant rules
redundant0=is.redundant(rules.trs)
which(redundant0)

##### drop dedundant rules
rules.trp=rules.trs[!redundant0]
plot(rules.trp)

###### Generate specific rules
inspect(rules.trp)
rulesspecial=apriori(trans4,parameter=list(minlen=2,support=0.5,confidence=0.5),
                     appearance=list(rhs=c("Milk","Bread"),default="lhs")     )
#Milk_rule=apriori(data=rules.trp,parameter = list(support=0.2,confidence=0.5,minlen=2),appearance = list(default="rhs",lhs="Milk"))

inspect(rulesspecial)

rulesspeciall=apriori(trans4,parameter=list(minlen=2,support=0.5,confidence=0.5),
                     appearance=list(lhs=c("Milk","Bread"),default="rhs"))
inspect(rulesspeciall)

plot(rulesspecial,measure = "confidence",method="graph",control = list(type="items"),shading = "lift")