Nature-inspiration on kernel machines: Data mining for continuous and discrete variables

Francisco J. Ruiz, Cecilio Angulo, Núria Agell

Producción científica: Capítulo del libroContribución a congreso/conferenciarevisión exhaustiva

Resumen

Kernel Machines, like Support Vector Machines, have been frequently used, with considerable success, in situations in which the input variables are given by real values. Furthermore, the nature of this machine learning algorithm allows esxtending its applications to deal with other kinds of systems with no vectorial information such as facial images, hand written texts, micro-array gene expressions, or protein chains. The behavior of a number of systems could be better explained if artificial infinite-precision variables were replaced by qualitative variables. Hence, the use of ordinal or interval scales on input variables would allow kernels to be defined for nature-inspired systems directly. In this contribution, two new kernels are designed for applying kernel machines to such systems described by qualitative variables (orders of magnitude or intervals). In addition, the structure of the feature space induced by this kernel is also analyzed.

Idioma originalInglés
Título de la publicación alojadaKnowledge-Based Intelligent Information and Engineering Systems - 10th International Conference, KES 2006, Proceedings
EditorialSpringer Verlag
Páginas425-432
Número de páginas8
ISBN (versión impresa)3540465375, 9783540465379
DOI
EstadoPublicada - 2006
Publicado de forma externa
Evento10th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2006 - Bournemouth, Reino Unido
Duración: 9 oct 200611 oct 2006

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen4252 LNAI - II
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349

Conferencia

Conferencia10th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2006
País/TerritorioReino Unido
CiudadBournemouth
Período9/10/0611/10/06

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