Intersection and signed-intersection kernels for intervals

Francisco J. Ruiz, Cecilio Angulo, Núria Agell

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Resumen

In this paper two kernels for interval data based on the intersection operation are introduced. On the one hand, it is demonstrated that the intersection length of two intervals is a positive definite (PD) kernel. On the other hand, a signed variant of this kernel, which also permits discriminating between disjoint intervals, is demonstrated to be a conditionally positive definite (CPD) kernel. The potentiality and performance of the two kernels presented when applying them to learning machine techniques based on kernel methods are shown by considering three different examples involving interval data.

Idioma originalInglés
Título de la publicación alojadaArtificial Intelligence Research and Development. Proceedings of the 11th International Conference of the Catalan Association for Artificial Intelligence
EditorialIOS Press
Páginas262-270
Número de páginas9
Edición1
ISBN (versión impresa)9781586039257
DOI
EstadoPublicada - 2008

Serie de la publicación

NombreFrontiers in Artificial Intelligence and Applications
Número1
Volumen184
ISSN (versión impresa)0922-6389

Huella

Profundice en los temas de investigación de 'Intersection and signed-intersection kernels for intervals'. En conjunto forman una huella única.

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