Online ensemble learning in the presence of concept drift

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http://eprints.org/relation/isVolatileVersionOf http://etheses.bham.ac.uk/id/document/3289 http://eprints.org/relation/ispreviewThumbnailVersionOf http://etheses.bham.ac.uk/id/document/3289 http://eprints.org/relation/isVersionOf http://etheses.bham.ac.uk/id/document/3289 archive 4031 disk0/00/00/13/34 2011-02-17 08:58:07 2019-01-23 09:53:57 2011-07-19 16:33:25 thesis show 0 Minku Leandro Lei Yao Xin 1962- University of Birmingham Online ensemble learning in the presence of concept drift unpub T1 LC 10col_ephy In online learning, each training example is processed separately and then discarded. Environments that require online learning are often non-stationary and their underlying distributions may change over time (concept drift). Even though ensembles of learning machines have been used for handling concept drift, there has been no deep study of why they can be helpful for dealing with drifts and which of their features can contribute for that. The thesis mainly investigates how ensemble diversity affects accuracy in online learning in the presence of concept drift and how to use diversity in order to improve accuracy in changing environments. This is the first diversity study in the presence of concept drift. The main contributions of the thesis are: - An analysis of negative correlation in online learning. - A new concept drift categorisation to allow principled studies of drifts. - A better understanding of when, how and why ensembles of learning machines can help to handle concept drift in online learning. - Knowledge of how to use information learnt from the old concept to aid the learning of the new concept. - A new approach called Diversity for Dealing with Drifts (DDD), which is accurate both in the presence and absence of drifts. 2011-07 2010-07 graduation eng author unchecked This unpublished thesis/dissertation is copyright of the author and/or third parties. The intellectual property rights of the author or third parties in respect of this work are as defined by The Copyright Designs and Patents Act 1988 or as modified by any successor legislation. Any use made of information contained in this thesis/dissertation must be in accordance with that legislation and must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the permission of the copyright holder. Overseas Research Students Awards Scheme The University of Birmingham public 188 University of Birmingham School of Computer Science d_ph other 2011-07 graduation