STAT 8250:Data Mining II

3 Class Hours 0 Laboratory Hours 3 Credit Hours
Prerequisite: STAT 8240
This course is a continuation of STAT 8240: Data Mining. Data Mining is an information extraction activity whose goal is to discover hidden facts contained in databases, perform prediction and forecasting, and generally improve their performance through interaction with data. The process includes data selection, cleaning, coding, using different statistical, pattern recognition and machine learning techniques, and reporting and visualization of the generated structures. The course will introduce additional modeling tools for pattern recognition and prediction, including Sequential Pattern Analysis, Neural Networks, Support Vector Machine, Nearest-neighbor classifiers, and many others. These tools will be taught through examples of practical applications. Students will be encouraged to try different Data Mining software.