STAT 8260:Segmentation Models

3 Class Hours 0 Laboratory Hours 3 Credit Hours
Prerequisite: STAT 7020 and (STAT 8320 or STAT 8240 ).
This class begins by reviewing classical clustering methods introduced in the data mining sequence. These methods are studied in greater depth and their application in massive data classification and market segmentation endeavors is explored. The second half of this course introduces the use of probabilistic models for segmentation, including mixture and latent class models, among others, and explores their utility and strengths. Segmentation using both continuous and categorical inputs with these methods is stressed. Further emphasis is placed on practical application of these methods when applied to massive data sources and appropriate and accurate reporting of results.