School of Computing

Seminars in the School of Computing

The school runs a highly successful annual programme of seminars given by guest speakers from academia and industry who are experts in their field. In addition, the school encourages an active seminar programme within its own research groups. These research group seminars may be given by guest speakers but typically act as a forum for members of the group to share their ideas.

School of Computing seminars take place in the Brian Spratt Room (SW101 Cornwallis South West). They are open to anyone in the University and visitors are especially welcome. Please contact Dr Rogério de Lemos for further information.

How to get to the University

Upcoming seminars

These are the School of Computing's upcoming seminars. Information on past seminars can be found here.

Feb 21, 2017
16:00 - 17:00
Approximate Feature Selection in Data-Driven Systems Modelling
School of Computing Seminars
Professor Qiang Shen (Aberystwyth University)

Title: Approximate Feature Selection in Data-Driven Systems Modelling


Feature selection (FS) addresses the problem of selecting those system descriptors that are most predictive of a given outcome. Unlike other dimensionality reduction methods, with FS the original meaning of the features is preserved. This has found application in tasks that involve datasets containing very large numbers of features that might otherwise be impractical to model and process (e.g., large-scale image analysis, text processing and Web content classification), where feature semantics play an important role.

This talk will focus on the development and application of approximate FS mechanisms based on rough and fuzzy-rough theories. Such techniques provide a means by which data can be effectively reduced without the need for user-supplied information. In particular, fuzzy-rough feature selection (FRFS) works with discrete and real-valued noisy data (or a mixture of both). As such, it is suitable for regression as well as for classification. The only additional information required is the fuzzy partition for each feature, which can be automatically derived from the data. FRFS has been shown to be a powerful technique for semantics-preserving data dimensionality reduction. In introducing the general background of FS, this talk will first cover the rough-set-based approach, before focusing on FRFS and its application to real-world problems. The talk will conclude with an outline of opportunities for further development.

Qiang Shen - URL :

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Cornwallis South West,
The University of Kent,
United Kingdom


Open to Anyone in the University and visitors are especially welcome,

Contact: Rogério de Lemos
School of Computing

School of Computing, University of Kent, Canterbury, Kent, CT2 7NF

Enquiries: +44 (0)1227 824180 or contact us.

Last Updated: 14/08/2015