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Scaling up classification rule induction through parallel processing

Published online by Cambridge University Press:  26 November 2012

Frederic Stahl  and
Max Bramer
Frederic Stahl
Affiliation:
School of Systems Engineering, University of Reading, Whiteknights, Reading RG6 6AY, UK; e-mail: [email protected]
Max Bramer
Affiliation:
School of Computing, University of Portsmouth, Buckingham Building, Lion Terrace, PO1 3HE Portsmouth, UK; e-mail: [email protected]
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Abstract

The fast increase in the size and number of databases demands data mining approaches that are scalable to large amounts of data. This has led to the exploration of parallel computing technologies in order to perform data mining tasks concurrently using several processors. Parallelization seems to be a natural and cost-effective way to scale up data mining technologies. One of the most important of these data mining technologies is the classification of newly recorded data. This paper surveys advances in parallelization in the field of classification rule induction.

Type
Articles
Information
The Knowledge Engineering Review , Volume 28 , Issue 4 , December 2013 , pp. 451 - 478
Copyright
Copyright © Cambridge University Press 2012 

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