Support vector learning for fuzzy rule-based classification systems.

Support vector learning for fuzzy rule-based classification systems.

To design a fuzzy rule-based classification system (fuzzy classifier) with good generalization ability in a high dimensional feature space has been an active research topic for a long time. As a powerful machine learning approach for pattern recognition problems, the support vector machine (SVM) is...

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Detalles Bibliográficos
Publicado en:IEEE Transactions on fuzzy systems 11, 6 (2003).
Autor Principal: Yixin Chen
Formato: Artigo
Idioma:English
Subjects:
Mercer kernel.
Fuzzy classifiers.
Fuzzy inference.
Fuzzy rule.
Fuzzy rule-based classification systems.
Generalization ability.
High-dimensional feature space.
Infinite dimensional feature space.
Kernel machines.
Machine learning.
Pattern recognition problems.
Positive definite fuzzy classifier.
Statistical learning theory.
Support vector learning.
Translation invariant kernel.