Isotropic Kernel Machine

Yann Guermeur () and Nicolas Wicker ()
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Yann Guermeur: LORIA-CNRS, Campus Scientifique
Nicolas Wicker: University of Lille

Sankhya A: The Indian Journal of Statistics, 2025, vol. 87, issue 2, No 7, 426-453

Abstract: Abstract A new kernel machine for multi-class pattern recognition is introduced: the isotropic kernel machine. It is designed to make use of the isotropy of the class conditional densities in the feature space. We provide theoretical guarantees on its generalization error. This error is then assessed empirically, in the framework of a comparative study.

Keywords: Margin multi-category classifiers; kernel machines; isotropy; Primary 62H30; Secondary 68Q32 (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s13171-025-00386-w

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