Mining local staircase patterns in noisy data

Author: Luc De Raedt, Ana Carolina Fierro, Tias Guns, International workshop on Co-Clustering and Applications, Thanh Le Van, Kathleen Marchal, Siegfried Nijssen, Matthijs van Leeuwen
Publisher: Institute of Electrical and Electronics Engineers (IEEE)

ABOUT BOOK

Most traditional biclustering algorithms identify biclusters with no or little overlap. In this paper, we introduce the problem of identifying staircases of biclusters. Such staircases may be indicative for causal relationships between columns and can not easily be identified by existing biclustering algorithms. Our formalization relies on a scoring function based on the Minimum Description Length principle. Furthermore, we propose a first algorithm for identifying staircase biclusters, based on a combination of local search and constraint programming. Experiments show that the approach is promising

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