A large number of clustering approaches have been proposed for the analysis of gene
expression data obtained from microarray experiments. However, the results from the …

DNA microarray technology has now made it possible to simultaneously monitor the
expression levels of thousands of genes during important biological processes and across …

The detection of correlations between different features in a set of feature vectors is a very
important data mining task because correlation indicates a dependency between the …

In high-dimensional data, clusters can exist in subspaces that hide themselves from
traditional clustering methods. A number of algorithms have been proposed to identify such …

Extensive studies have shown that mining microarray data sets is important in bioinformatics
research and biomedical applications. In this paper, we explore a novel type of gene-sample …

A bicluster of a gene expression dataset captures the coherence of a subset of genes and a
subset of conditions. Biclustering algorithms are used to discover biclusters whose subset of …

Motivation: Analysis of gene expression data can provide insights into the positive and
negative co-regulation of genes. However, existing methods such as association rule mining …

Unlike traditional clustering methods that focus on grouping objects with similar values on a
set of dimensions, clustering by pattern similarity finds objects that exhibit a coherent pattern …

Traditional clustering is a descriptive task that seeks to identify homogeneous groups of
objects based on the values of their attributes. While domain knowledge is always the best …

本文提出了一个基于数据挖掘聚类技术的信用评分评级方法. 该方法使用数据挖掘的聚类算法,
对传统信用评分模型进行了改进, 本文给出了方法的理论证明, 并在一个信用卡分析系统DMCA …