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 ...

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, ...

Step 1: Handling of incomplete data Incomplete data affects classification accuracy and hinders effective data mining. The following techniques are effective for working with incomplete data.

Data mining tools collect and analyze data much faster than humans. Learn what data mining is, how it works, and how to use it effectively.