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.