#Prepare a data.frame to dump outcomes
output<-data.frame(Item=rep(NA, 169), Numberi=rep(NA,169),Numberi_Wholemilk=rep(NA,169),Confidence=rep(NA,169),Lift=rep(NA,169))


#Get support for whole milk
support.wholemilk <- sum(Groceries[,25]==1) / length(Groceries[,25])

#Loop through all columns, skip column 25 as this contains whole milk
for(i in 1:169){
  
  output[i,1]<- colnames(Groceries)[i]
  
  if(i != 25){
    support_i_wholemilk = sum(Groceries[,i]==1 & Groceries[,25]==1) / length(Groceries[,i])
    support_i = sum(Groceries[,i]==1) / length(Groceries[,i])
    confidence = support_i_wholemilk / support_i
    lift = confidence / support.wholemilk

    output[i,2] = sum(Groceries[,i]==1)
    output[i,3] = sum(Groceries[,i]==1 & Groceries[,25]==1)
    output[i,4] = confidence
    output[i,5] = lift
  }
}

#Sort the outptu data.frame by lift, largest to smallest
output[order(-1*output[,5]),]



#Arules code
library(arules)

#All variaables must be factors, forcing factor level on each column
for(i in 1:169){
  Groceries[,i] <- as.factor(Groceries[,i])
}

#Forcing Groceries to a transaction object
gr.trans = as(Groceries,"transactions")

#Rule development vai apriori function
gr.rules = apriori(gr.trans, parameter = list(supp = 0.0, conf = 0.0, maxlen=2))

#Rules that have whole milk on right side
gr.subset = subset(gr.rules, subset = rhs %in% "wholemilk=1")

#Print rules to screen - sorted by lift
inspect(sort(gr.subset,by="lift"))


#Rule development vai apriori function
gr.rules = apriori(gr.trans, parameter = list(supp = 0.01, conf = 0.25, maxlen=2))
#Print rules to screen - sorted by lift
outcomes<-inspect(sort(gr.rules,by="lift"))

#Looking at top 10
outcomes[1:10,]


#Rule development vai apriori function
gr.rules = apriori(gr.trans, parameter = list(supp = 0.01, conf = 0.25, maxlen=2))
#Print rules to screen - sorted by lift
outcomes<-head(sort(gr.rules,by="lift"),20)

library(arulesViz)
plot(outcomes, method="grouped")


#BobRoss A Rules analysis
#Create a subset to inclue only the feature columns
BobRoss2 <- BobRoss[,5:71]

#All variaables must be factors, forcing factor level on each column
for(i in 1:67){
  BobRoss2[,i] <- as.factor(BobRoss2[,i])
}

#Forcing Groceries to a transaction object
gr.trans = as(BobRoss2,"transactions")

#Rule development vai apriori function
gr.rules = apriori(gr.trans, parameter = list(supp = 0.05, conf = 0.20, maxlen=3))


#Rules that have whole milk on right side
#gr.subset = subset(gr.rules, subset = rhs %in% "wholemilk=1")

#Print rules to screen - sorted by lift
output <- inspect(sort(gr.rules,by="lift")[1:10])


#Print rules to screen - sorted by lift
output <- head(sort(gr.rules,by="lift"),20)

library(arulesViz)
plot(output,method="grouped")