An approximation ratio for biclustering

The problem of biclustering consists of the simultaneous clustering of rows and columns of a matrix such that each of the submatrices induced by a pair of row and column clusters is as uniform as possible. In this paper we approximate the optimal biclustering by applying one-way clustering algorithms independently on the rows and on the columns of the input matrix. We show that such a solution yields a worst-case approximation ratio of 1+ 2 under L1-norm for 0

• Type: Journal
• Year: 2008
• Where: IPL
• Authors: Kai Puolamäki, Sami Hanhijärvi, Gemma C. Garriga
• Keywords: Columns, IPL 2008, One-way Clustering Algorithms, Simultaneous Clustering