Methods for the combination of kernel matrices within a support vector framework

DOI10.1007/s10994-009-5135-5zbMath1470.68144OpenAlexW1977425532MaRDI QIDQ1959546

Isaac Martín de Diego, Javier M. Moguerza, Alberto Muñoz

Publication date: 7 October 2010

Published in: Machine Learning (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10994-009-5135-5

zbMATH Keywords

kernel methodssupport vector machinessimilarity-based classificationcombination of kernels

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05)

Related Items (3)

A nested heuristic for parameter tuning in support vector machines ⋮ Supervised classification and mathematical optimization ⋮ Polar Classification of Nominal Data

Uses Software

• UCI-ml

Cites Work

• Metric and Euclidean properties of dissimilarity coefficients
• Support-vector networks
• 10.1162/15324430260185592
• The Dissimilarity Representation for Pattern Recognition
• Models for asymmetric proximities
• Asymptotic Behaviors of Support Vector Machines with Gaussian Kernel
• Semidefinite Programming
• Structural, Syntactic, and Statistical Pattern Recognition
• Structural, Syntactic, and Statistical Pattern Recognition
• The elements of statistical learning. Data mining, inference, and prediction
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