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9

ESANN
2007

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Interval discriminant analysis using support vector machines

13 years 5 months ago

Interval discriminant analysis using support vector machines

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Imprecision, incompleteness, prior knowledge or improved learning speed can motivate interval–represented data. Most approaches for SVM learning of interval data use local kernels based on interval distances. We present here a novel approach, suitable for linear SVMs, which allows to deal with interval data without resorting to interval distances. The experimental results conﬁrms the validity of our proposal.

Cecilio Angulo, Davide Anguita, Luis Gonzál

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ESANN 2007 | Interval Data | Interval Distances | Neural Networks | SVM Learning |

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Added	29 Oct 2010
Updated	29 Oct 2010
Type	Conference
Year	2007
Where	ESANN
Authors	Cecilio Angulo, Davide Anguita, Luis González

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