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Exploiting system structure in data-driven predictive analytics


Webinar on

Exploiting system structure in data-driven predictive analytics

7th July 2022 at 3pm (UK time)


Current predictive analytics approaches are strongly focused on optimizing accuracy metrics, leaving little room to incorporate a priori knowledge about the processes under analysis and relegating to a secondary concern the interpretation of results. However, in the analysis of complex systems, one of the main interests is precisely the induction of relevant associations, in order to understand or clarify the way systems operate. On the other hand, there is often information available regarding the structure of the processes, which could be used in benefit of the analysis and to enhance the interpretation of results.

The importance of this issue is not new and has motivated the development of multiblock approaches that try to improve the interpretation of results, while maintaining the quality of predictions. In this talk, two classes of multiblock frameworks are addressed, that present interpretational-oriented features, while allowing some system structure to be incorporated. One class is based on the existence of a priori knowledge for building the blocks of variables, while the other is able to extract the system structure in a data-driven way.

This webinar will be presented by Marco Reis, University of Coimbra, Portugal.


The webinar will last no longer than one hour.

To register please contact christine.stevenson@strath.ac.uk

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