Generalizing Version Space Support Vector Machines for Non-Separable Data

Authors:
E. N. Smirnov;I. G. Sprinkhuizen-Kuyper;N. I. Nikolaev
Affiliations:
Maastricht University, Netherlands;Maastricht University, Netherlands;University of London, UK
Venue:
ICDMW '06 Proceedings of the Sixth IEEE International Conference on Data Mining - Workshops
Year:
2006

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Abstract

Although version space support vector machines (VSSVMs) are a successful approach to reliable classification [6], they are restricted to separable data. This paper proposes generalized VSSVMs (GVSSVMs) applicable for separable and non-separable data. We show that GVSSVMs can outperform existing reliable-classification approaches.