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 ...

Here, appropriate data mining algorithms are selected based on the goal of the mining — e.g., classification, regression, clustering, etc. Different algorithms are better suited for different ...

Clustering algorithms are a powerful form of AI that can be applied to business challenges from customer segmentation to fraud detection.

Faulty data mining makes seeking of decisive information akin to finding a needle in a haystack. Here are some tips to tweak your data mining exercises.

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, ...