Need your help to find all matched item in LHS of Apriori(R)

machine_learning
data_mining
data_science
apriori_algorithm
technique

#1

Hi Expert,

Hello Everyone!

I run the apriori to find association between product and item purchased.

Product     Item1    Item2  Item3  Item4   Item5  Item6
Biscuit        1    	0	0	1	1	1
Soap	       1	1	1	1	1	1
Tea	       1	0	0	0	0	0
Biscuit 	1	0	1	0	0	0
Soap	        1	1	1	0	0	0
Biscuit 	1	0	0	0	0	0

Now how can I set LHS or RHS such that I will get all product list when condition for all items are true (i.e. item1=1 and item2=1 and item3=1 and item4=1 and item5=1 and item6=1).
Along with this, the program should retrieve all products when more than or equal to 50% of item are satisfied.
I use subset to capture all items=1 but its not working.

library(arules)
prod_item = read.csv(“D:/name.csv”)
df_trans = as(prod_item,‘transactions’)
rules = apriori(df_trans,parameter = list(minlen=5,support=0.5, confidence=0.5))

I use minlen=5 to satisfy more than 5 condition true.