Multiclass Classification with Multi-Prototype Support Vector Machines
Abstract
Winner-take-all multiclass classifiers are built on the top of a set of prototypes each representing one of the available classes. A pattern is then classified with the label associated to the most 'similar' prototype. Recent proposal of SVM extensions to multiclass can be considered instances of the same strategy with one prototype per class.
Cite
Text
Aiolli and Sperduti. "Multiclass Classification with Multi-Prototype Support Vector Machines." Journal of Machine Learning Research, 2005.Markdown
[Aiolli and Sperduti. "Multiclass Classification with Multi-Prototype Support Vector Machines." Journal of Machine Learning Research, 2005.](https://mlanthology.org/jmlr/2005/aiolli2005jmlr-multiclass/)BibTeX
@article{aiolli2005jmlr-multiclass,
title = {{Multiclass Classification with Multi-Prototype Support Vector Machines}},
author = {Aiolli, Fabio and Sperduti, Alessandro},
journal = {Journal of Machine Learning Research},
year = {2005},
pages = {817-850},
volume = {6},
url = {https://mlanthology.org/jmlr/2005/aiolli2005jmlr-multiclass/}
}