Support vector machines over a discrete structure: A kernel for qualitative orders of magnitude spaces

Núria Agell Jané, Francesc Prats Duaygues, Rosario Rovira Llobera, Mònica Sánchez Soler

Research output: Book chapterChapter

Abstract

This paper is within the domain of the study of learning algorithms based on kernels, precisely of the Support Vector Machines. a kernel is constructed over the discrete structure of absolute orders of magnitude spaces. This kernel is based on an explicit function, defined from the space of k-tuples of qualitative labels to a feature space, which captures the remoteness between the components of the patterns by using certain weights exponentially. a simple example that allows interpreting the kernel in terms of proximity of the patterns is presented.
Original languageEnglish
Title of host publicationArtificial intelligence research and development
Pages267-275
Publication statusPublished - 1 Jan 2003

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