Given the increased pervasiveness of data analytics tasks in almost every area of life and their increasing complexity, we are now often facing tasks of structured output prediction. Situated within the areas of data mining and machine learning, structured output prediction is concerned with predicting complex structured values (e.g., vectors of real numbers) rather than a scalar value (e.g., a single real number). Examples of such tasks include multi-target prediction (e.g., multi-target classification and multi-target regression), multi-label classification and hierarchical multi-label classification.
The course will introduce the 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. The course is practically oriented and requires students to apply predictive analythics methods for structured data in the context of their research work
