what algorithm for rules mining in itemsets

Question

I have following data, every entry contains an itemset and to which class it belongs to (positive or negative).

What algorithm I can use to find out that what combination of items indicate positive or negative?

In the following case, I want to find out that (B, C) indicate positive and (D, E) indicate negative.

B, C, A -> positive

B, C, D -> positive

B, C, E -> positive

B, D, E -> negative

C, D, E -> negative

A, D, E -> negative

result: (B, C) indicate positive, (D, E) indicate negative.

I've tried frequent itemsets and apriori, result is not good, is there any other possible method?

Answer 1

One typical algorithm could be mapping each pair of items in each record ( itemset ) into its positive or negative class and then count the number of mappings to either positive nor negative classes and compare the results to know which number is greater. That's the class you are looking for each pair.

It's very costly especially when your itemsets have large number of items reside in so, generally, you need some sort of data structures to store and retrieve data in fast and efficient way.