PASCAL2 Invited talk:

Ludmila Kuncheva,
University of Wales, Bangor, UK
Classifier Ensembles for Detecting Concept Change in Streaming Data: Overview and Perspectives

Abstract We address adaptive classification of streaming data in the presence of concept change. An overview of the machine learning approaches reveals a deficit of methods for explicit change detection. Typically, classifier ensembles designed for changing environments do not have a bespoke change detector. Here we take a systematic look at the types of changes in streaming data and at the current approaches and techniques in online classification. Classifier ensembles for change detection are discussed. An example is carried through to illustrate individual and ensemble change detectors for both unlabelled and labelled data. While this paper does not offer ready-made solutions, it outlines possibilities for novel approaches to classification of streaming data.