Detecting Subclusters in Outliers
Dongseok
Choi
Thursday, March 7, 2013 - 3:30pm

In medical research, it is often interested in finding subgroups in an outlier group. For example, a certain medical condition can be more frequent in a small group that is different from the majority of population. One approach to find groups in a data set is using cluster analysis. Cluster analysis has been widely used tool in exploring potential group structure in complex data and has received greater attention in recent years due to data mining and high dimensional data such as microarrays. In this presentation, I will introduce split-and-recombine procedure and its application for a medical data set. In addition, analysis results of the same data using other clustering methods will be discussed.