I'm looking at datasets where the the attributes and the target class have a logical relationsships. All attributes and the target class are binary.
Here's an example: Neither
feature#2 have a significant correlation with the target class. But the conjunction
feature#1 AND feature#2 is correlated with the target class.
Are there any Feature Selection Algorithms able to cope with situations like that? I'm thinking that frequent itemsets could be useful. It would be tremendously helpful, if anyone could point me to a related paper.