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The Impact of Latency on Online Classification Learning with Concept Drift

Marrs, Gary R., Hickey, RJ and Black, Michaela (2010) The Impact of Latency on Online Classification Learning with Concept Drift. In: The fourth International Conference on Knowledge Science, Engineering and Management (KSEM`2010), Belfast, Northern Ireland. Springer Berlin / Heidelberg. Vol 6291/2 10 pp. [Conference contribution]

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URL: http://www.springerlink.com/content/91103633n6hgrr7m/

DOI: 10.1007/978-3-642-15280-1_42

Abstract

Online classification learners operating under concept drift can be subject to latency in examples arriving at the training base. A discussion of latency and the related notion of example filtering leads to the development of an example life cycle for online learning (OLLC). Latency in a data stream is modelled in a new Example Life-cycle Integrated Simulation Environment (ELISE). In a series of experiments, the online learner algorithm CD3 is evaluated under several drift and latency scenarios. Results show that systems subject to large random latencies can, when drift occurs, suffer substantial deterioration in classification rate with slow recovery.

Item Type:Conference contribution (Paper)
Keywords:Online Learning - Classification - Concept Drift - Data stream - Example life-cycle - Latency - ELISE - CD3
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Information Engineering
Research Institutes and Groups:Computer Science Research Institute
Computer Science Research Institute > Information and Communication Engineering
ID Code:18791
Deposited By: Dr Michaela Black
Deposited On:22 Jun 2011 14:21
Last Modified:09 Dec 2015 10:57

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