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2007

Kernel-based online machine learning and support vector reduction

8 years 11 months ago
Kernel-based online machine learning and support vector reduction
We apply kernel-based machine learning methods to online learning situations, and look at the related requirement of reducing the complexity of the learnt classifier. Online methods are particularly useful in situations which involve streaming data, such as medical or financial applications. We show that the concept of span of support vectors can be used to build a classifier that performs reasonably well while satisfying given space and time constraints, thus making it potentially suitable for such online situations. The span-based heuristic is observed to be effective under stringent memory limits (that is when the number of support vectors a machine can hold is very small). r 2008 Elsevier B.V. All rights reserved.
Sumeet Agarwal, V. Vijaya Saradhi, Harish Karnick
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2007
Where ESANN
Authors Sumeet Agarwal, V. Vijaya Saradhi, Harish Karnick
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