Wouter Duivesteijn
For years Wouter claimed to be a mathematician who also happens to do computer science.
After receiving his Master's degrees with a final thesis on a data mining subject, he finally
converted to computer science in 2009, when he became a Ph.D. student in the Algorithms group
of LIACS. Each week he spends two days in the ADA group.
Wouter is working on the NWO Exceptional Model Mining (EMM) project.
EMM is a framework that can be seen as a generalisation of Subgroup Discovery (SD).
Both SD and EMM attempt to find small portions of the data where the observed behaviour is
notably different from that of the database as a whole. But, whereas in SD `behaviour' is
traditionally interpreted in terms of the distribution of a single nominal variable, EMM seeks
subgroups for which the fitted local model is surprisingly different from the global model.
In this approach, `behaviour' is described by a number of attributes, and fitting a model
captures the multivariate dependencies between these attributes.
Selected Refereed Publications
2010 |
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Subgroup Discovery meets Bayesian networks – an Exceptional Model Mining approach. In: Proceedings of the 10th IEEE International Conference on Data Mining (ICDM'10), 2010. |
2008 |
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Nearest Neighbour Classification with Monotonicity Constraints. In: Proceedings of the European Conference on Machine Learning and Principles and Practices of Knowledge Discovery in Data 2008 Part I (ECML PKDD'08), pp 301-316, 2008. |