Kernels for Structured Data
Date
2003
Authors
Gaertner, Thomas
Lloyd, John
Flach, Peter
Journal Title
Journal ISSN
Volume Title
Publisher
Springer
Abstract
Learning from structured data is becoming increasingly important. However, most prior work on kernel methods has focused on learning from attribute-value data. Only recently have researchers started investigating kernels for structured data. This paper describes how kernel definitions can be simplified by identifying the structure of the data and how kernels can be defined on this structure. We propose a kernel for structured data, prove that it is positive definite, and show how it can be adapted in practical applications.
Description
Keywords
Keywords: Attribute-value data; Kernel definitions; Kernels; Structured data; Artificial intelligence; Data reduction; Data structures; Logic programming; Learning systems
Citation
Collections
Source
Inductive Logic Programming: Revised Papers of 12th International Conference, ILP 2002
Type
Conference paper