Error Bounds for Kernel Fisher Linear Discriminant in Gaussian Hilbert Space
Abstract
We give a non-trivial, non-asymptotic upper bound on the classification error of the popular Kernel Fisher Linear Discriminant classifier under the assumption that the kernel-induced space is a Gaussian Hilbert space.
Cite
Text
Durrant and Kaban. "Error Bounds for Kernel Fisher Linear Discriminant in Gaussian Hilbert Space." Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012.Markdown
[Durrant and Kaban. "Error Bounds for Kernel Fisher Linear Discriminant in Gaussian Hilbert Space." Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012.](https://mlanthology.org/aistats/2012/durrant2012aistats-error/)BibTeX
@inproceedings{durrant2012aistats-error,
title = {{Error Bounds for Kernel Fisher Linear Discriminant in Gaussian Hilbert Space}},
author = {Durrant, Robert and Kaban, Ata},
booktitle = {Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics},
year = {2012},
pages = {337-345},
volume = {22},
url = {https://mlanthology.org/aistats/2012/durrant2012aistats-error/}
}