Kernels for the Relevance Vector Machine - An empirical study

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    2 Scopus citations

    Abstract

    The Relevance Vector Machine (RVM) is a generalized linear model that can use kernel functions as basis functions. Experiments with the Matérn kernel indicate that the kernel choice has a significant impact on the sparsity of the solution. Furthermore, not every kernel is suitable for the RVM. Our experiments indicate that the Matérn kernel of order 3 is a good initial choice for many types of data.

    Original languageEnglish
    Title of host publicationAdvances in Web Intelligence and Data Mining
    EditorsMark Last, Piotr Szczepaniak, Piotr Szczepaniak, Zeev Vlvolkov, Abraham Kandel
    Pages253-263
    Number of pages11
    DOIs
    StatePublished - 27 Sep 2006

    Publication series

    NameStudies in Computational Intelligence
    Volume23
    ISSN (Print)1860-949X

    Keywords

    • Kernel Regression
    • Machine learning
    • Relevance vector machine
    • matérn kernel

    ASJC Scopus subject areas

    • Artificial Intelligence

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