日本語
 
Help Privacy Policy ポリシー/免責事項
  詳細検索ブラウズ

アイテム詳細


公開

会議論文

An Improved Training Algorithm for Kernel Fisher Discriminants

MPS-Authors
There are no MPG-Authors in the publication available
External Resource
Fulltext (restricted access)
There are currently no full texts shared for your IP range.
フルテキスト (公開)
公開されているフルテキストはありません
付随資料 (公開)
There is no public supplementary material available
引用

Mika, S., Schölkopf, B., & Smola, A. (2001). An Improved Training Algorithm for Kernel Fisher Discriminants. In T., Richardson, & T., Jaakkola (Eds.), 8th International Conference on Artificial Intelligence and Statistics (AISTATS 2001) (pp. 98-104). Society for Artificial Intelligence and Statistics.


引用: https://hdl.handle.net/11858/00-001M-0000-0013-E30C-2
要旨
We present a fast training algorithm for the kernel Fisher discriminant classifier. It uses a greedy approximation technique and has an empirical scaling behavior which improves upon the state of the art by more than an order of magnitude, thus rendering the kernel Fisher algorithm a viable option also for large datasets.