Intersection and signed-intersection kernels for intervals

Francisco J. Ruiz, Cecilio Angulo, Núria Agell

Producció científica: Capítol de llibreContribució a congrés/conferènciaAvaluat per experts


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 originalAnglès
Títol de la publicacióArtificial Intelligence Research and Development. Proceedings of the 11th International Conference of the Catalan Association for Artificial Intelligence
EditorIOS Press
Nombre de pàgines9
ISBN (imprès)9781586039257
Estat de la publicacióPublicada - 2008

Sèrie de publicacions

NomFrontiers in Artificial Intelligence and Applications
ISSN (imprès)0922-6389


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