• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.5
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• pp.569-574
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• 2011

In this paper, we introduce the subspace contrasting group identification problem and propose an algorithm to solve the problem. In order to identify contrasting groups, the algorithm first determines two groups of which attribute values are in one of the contrasting ranges specified by the analyst, and searches for the contrasting groups while increasing the dimension of subspaces with an association rule mining strategy. Because the dimension of microarray data is likely to be tens of thousands, it is burdensome to find all contrasting groups over all possible subspaces by query generation. It is very useful in the sense that the proposed method allows to find those contrasting groups without analyst's involvement.