• Course code:63835B
  • Credits:5
  • Semester: summer
  • Contents

Predictive Analytics for Structured Data

The course will introduce the students to different tasks of structured output prediction and describe a variety of approaches for solving such tasks. The students will get to know some state-of-the-art tools for solving such tasks and examples of their use in practice. Within the course, the students will learn to apply predictive analytics methods for structured data in the context of their research.

 The course will cover the following topics:

  1. The different tasks of structured output prediction, such as multi-target classification/ regression and (hierarchical) multi-label classification.
  2. Predictive clustering methods (tree and rule-based) for structured output prediction.
  3. Ontologies for data mining and their use for describing structured output prediction.
  4. Ensemble methods for structured output prediction (tree and rule ensembles).
  5. Applications of structured output prediction to different practical problems, from areas such as environmental/ life sciences and image annotation/ retrieval.
  • Study programmes
  • Distribution of hours per semester
15
hours
lectures
15
hours
laboratory work
  • Professor
Course Organiser
Room:R2.07