6533b824fe1ef96bd1281291

RESEARCH PRODUCT

Fuzzy sigmoid kernel for support vector classifiers

Gustau Camps-vallsEmilio Soria-olivasJosé D. Martín-guerreroJosé Luis Rojo-álvarez

subject

business.industryCognitive NeurosciencePattern recognitionSigmoid functionFuzzy logicComputer Science ApplicationsSupport vector machineKernel methodArtificial IntelligencePolynomial kernelKernel embedding of distributionsRadial basis function kernelLeast squares support vector machineArtificial intelligencebusinessMathematics

description

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.

yearjournalcountryeditionlanguage
2004-12-01Neurocomputing
https://doi.org/10.1016/j.neucom.2004.07.004