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Co-clustering is a data mining technique used to extract the underlying blockstructure between the rows and columns of a data matrix. Many approaches havebeen studied and have shown their capacity to extract such structures incontinuous, binary or contingency tables. However, very little work has beendone to perform co-clustering on mixed type data. In this article, we extendthe latent block models based co-clustering to the case of mixed data(continuous and binary variables). We then evaluate the effectiveness of theproposed approach on simulated data and we discuss its advantages and potentiallimits.

Model Based Co-clustering of Mixed Numerical and Binary Data