Fuzzy sigmoid kernel for support vector classifiers

Abstract:

This Letter proposes the use of the fuzzy sigmoid function presented in (IEEE Trans. Neural Networks 14(6) (2003) 1576) as non-positive semi-definite kernel in the support vector machines framework. The fuzzy sigmoid kernel allows lower computational cost, and higher rate of positive eigenvalues of the kernel matrix, which alleviates current limitations of the sigmoid kernel. © 2004 Elsevier B.V. All rights reserved.

Año de publicación:

2004

Keywords:

• SUPPORT VECTOR MACHINES
• Positive semi-definite kernel
• sigmoid

Fuente:

scopus