The Sonoma State University Department of Mathematics and Statistics Presents Cristina Tortora, San Jose State University. Cluster analysis is a data analysis technique with the goal of grouping a set of objects in such a way that objects in a cluster are more similar to each other than to those in other clusters. For example, using cluster analysis, one can find groups of patients with similar symptoms. In this talk, I’ll give an introduction to cluster analysis focusing on model-based clustering, a specific subgroup of cluster analysis techniques. Model-based clustering uses density functions to model each cluster within the data; the entire data set is defined as a convex combination of the clusters. I’ll then focus on some challenges and recent advancements in model-based clustering with examples in different fields.

Series supported by Instructionally-Related Activities Funds. For more information about this series, go to www.sonoma.edu/math