Correspondences between fuzzy equivalence relations and kernels: Theoretical results and potential applications

Bernhard Moser, Ulrich Bodenhofer

Publikation: Beitrag in Buch/Bericht/TagungsbandKonferenzbeitragBegutachtung

Abstract

Kernels have proven useful for machine learning, data mining, and computer vision as they provide a means to derive non-linear variants of learning, optimization or classification strategies from linear ones. A central question when applying a kernel-based method Is the choice and the design of the kernel function. This paper provides a novel view on kernels based on fuzzy logical concepts that allows to Incorporate prior knowledge In the design process. It Is demonstrated that kernels that map to the unit Interval and have constantly 1 In their diagonals can be represented by a commonly used fuzzy-logical formula for representing fuzzy relations. This means that a large and Important class of kernels can be represented by fuzzy logical concepts. Beside this result which only guarantees the existence of such a representation, constructive examples are presented.

OriginalspracheEnglisch
Titel2006 IEEE International Conference on Fuzzy Systems
Seiten2171-2177
Seitenumfang7
DOIs
PublikationsstatusVeröffentlicht - 2006
Extern publiziertJa
Veranstaltung2006 IEEE International Conference on Fuzzy Systems - Vancouver, BC, Kanada
Dauer: 16 Juli 200621 Juli 2006

Publikationsreihe

NameIEEE International Conference on Fuzzy Systems
ISSN (Print)1098-7584

Konferenz

Konferenz2006 IEEE International Conference on Fuzzy Systems
Land/GebietKanada
OrtVancouver, BC
Zeitraum16.07.200621.07.2006

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