Co-clustering algorithms and models represent a robust framework for the simultaneous partitioning of the rows and columns in a data matrix. This dual clustering approach, often termed block ...

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Successful completion of this course demonstrate your achievement of the following learning outcomes for the MS-DS program: Identify the core functionalities of data modeling in the data mining ...

Incomplete data affects classification accuracy and hinders effective data mining. The following techniques are effective for working with incomplete data. The ISOM-DH model handles incomplete data ...

Statistica Sinica, Vol. 12, No. 1, A Special Issue on Bioinformatics (January 2002), pp. 241-262 (22 pages) Many clustering algorithms have been used to analyze microarray gene expression data. Given ...

We introduce a novel statistical procedure for clustering categorical data based on Hamming distance (HD) vectors. The proposed method is conceptually simple and computationally straightforward, ...