Laboratoire de Génie Informatique et d’Automatique de l’Artois


Pattern classification based on belief function theory

Le 19 juin 2017 à 14h00 Salle des séminaires du LGI2A, FSA, Béthune
Zhunga LIU Maître de conférences Northwestern Polytechnical University, Xi'an, China
Le séminaire est présenté en anglais.

In the complex pattern classification problem, how to well deal with the uncertainty remains an interesting and important research topic. Belief function theory provides an efficient tool to represent and combine the uncertain information, and it is employed here for pattern classification. In this talk, we will present three parts of our recent work on the belief-based pattern classification :

  1. credal classification of incomplete pattern with missing attributes
  2. credal c-means clustering method for the partly overlapping data and
  3. classifier fusion with refined reliability evaluation under the power-set.

We will also discuss some potential research work with belief functions in the final.