Science - Course - Introduction to Data Mining

This course introduces and studies the concepts, issues, tasks and techniques of data mining. Topics include data preparation and feature selection, decision tables, decision trees, classification rules, association rules, clustering, statistical modeling, and linear models. Pre-req.: CMPS 342 & Math 250. * The practical part of this course, provided by the department of Mathematics and Computer Science, will be adjusted accordingly for the group of Biology/Biochemistry students enrolled in the Computational Biology track. The laboratory part features an introduction to popular data mining problems and algorithms, reaching from classification to clustering. Based on these techniques, we examine how these algorithms can be used to study gene expression, protein function or the structure of biological networks.