Clustering in Multivariate Data : Visualization, Case and Variable Reduction

                        Sunhee Kwon
                      Iowa State University 


Cluster analysis is a very common problem for multivariate data.  It is
receiving intense attention due to the current boom in data
warehousing and mining driven by the growth in information technology
today.  Technology is allowing us to collect massive data sets, both in
cases and variables, and develop sophisticated interactive and dynamic
graphics.  There are three current issues for cluster analysis :
visualizing cluster structure, reducing the number of cases, and
reducing the number of variables in very large data sets.  This thesis
addresses each of these issues.