MATHEMATICS AND STATISTICS COLLOQUIUM
Thursday, November 14, 2019, 4:00 PM, Davis 301
Refreshments at 3:30 PM, Davis 2nd floor
Exploring and Evaluating Patterns in Data Through Model-Based Clustering and Partition Agreement
Clustering is a method of unsupervised machine learning that seeks to uncover group structure in data by classifying observations when little or no a priori information about groups is available. In this talk, I will introduce the audience to statistical clustering with a special focus on model-based clustering and model assessment via partition agreement.