Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
536466 | Pattern Recognition Letters | 2012 | 10 Pages |
In this paper, we present a hypergraph based geometric biclustering (HGBC) algorithm. In a high dimensional space, bicluster patterns to be recognized can be considered to be linear geometrical structures. We can use the Hough transform (HT) to find sub-biclusters which correspond to the linear structures in column-pair spaces. Then a hypergraph model is built to merge the sub-biclusters into larger ones. Experiments on simulated and real biological data show that the HGBC algorithm proposed here can combine the sub-biclusters efficiently and provide more accurate classification results compared with existing biclustering methods.
► We proposed a new hypergraph based geometric biclustering algorithm in this article. ► We used Hough transform in order to find column-pair sub-biclusters. ► Hypergraph partitioning tool is applied to decrease the sub-bicluster combining time. ► Experiment shows our method is more efficient and accurate for bicluster detection.