Teacher:  Zhirong Yang, HIIT (zhirong.yang at helsinki.fi) 

Scope: 5 op

Type: advanced studies

Teaching: seminar / to pass the course:

1. attend at least 80% of the classes
2. make an oral presentation on a chosen topic
3. small project: implement the methods in another topic and write a report
4. review two reports by other students

• Grading: attendance (10%), reviewing (20%), small project (30%), presentation (40%)

Topics: Cluster analysis or clustering is the task of grouping a set of objects in such a way that objects in the same group are more similar to each other than to those in other groups. Cluster analysis is a main task of exploratory data mining, and a common technique for statistical data analysis used in many fields. In this seminar, we will discuss various topics in cluster analysis, from basic concepts and classical algorithms, to various new challenges and new methods.

Material: PDF textbook  Brian S. Everitt, Sabine Landau, Morven Leese and  Daniel Stahl. Cluster Analysis. 5nd Edition. Wiley. 2011 + a collection of research articles