Generalizing Version Space Support Vector Machines for Non-Separable Data. E.N. Smirnov. MICC-IKAT. Maastricht University. Maastricht 6200 MD. The Netherlands.
This paper proposes generalized VSSVMs (GVSSVMs) applicable for separable and non-separable data. We show that GVSSVMs can outperform existing reliable-�...
It is shown that GVSSVMs can outperform existing reliable-classification approaches. Although version space support vector machines (VSSVMs) are a�...
Although version space support vector machines (VSSVMs) are a successful approach to reliable classification, they are restricted to separable data.
Generalizing Version Space Support Vector Machines for Non ...
dl.acm.org › doi › abs › ICDMW.2006.86
This paper proposes generalized VSSVMs (GVSSVMs) applicable for separable and non-separable data. We show that GVSSVMs can outperform existing reliable-�...
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Generalizing Version Space Support Vector Machines for Non-Separable Data � Meta-conformity approach to reliable classification � Learning valued preference�...
Feb 19, 2024 � In this piece, we turn our attention to the application of SVMs to non-separable datasets, going beyond the mere absence of linear separability.
