Apriori algorithm to generate all rules using R

Question

Here is my R code for generating association rules using arules package in R

c1 <- c("A","F","D","B")
c2 <- c("D","B","A","C","E")
c3 <- c("C","B","A","E")
c4 <- c("B","D","A")

transactions <- list(c1,c2,c3,c4)

rules_b <- apriori(transactions, parameter = list(supp = 0.6, conf = 0.8, target = "rules"))

I'm getting just 8 rules as a result.

> inspect(rules_b)
  lhs      rhs support confidence lift
1 {}    => {B} 1.00    1          1   
2 {}    => {A} 1.00    1          1   
3 {D}   => {B} 0.75    1          1   
4 {D}   => {A} 0.75    1          1   
5 {B}   => {A} 1.00    1          1   
6 {A}   => {B} 1.00    1          1   
7 {B,D} => {A} 0.75    1          1   
8 {A,D} => {B} 0.75    1          1  

If we solve this, we can also get D => {A,B} as a rule. But, it's not displaying in this program. What's wrong in my code?

Answer 1

Does this(?apriori) answer your question?

Note: Apriori only creates rules with one item in the RHS (Consequent)!