Minimum error classification with geometric margin control

Hideyuki Watanabe*, Shigeru Katagiri, Kouta Yamada, Erik McDermott, Atsushi Nakamura, Shinji Watanabe, Miho Ohsaki

*この研究の対応する著者

研究成果: Conference contribution

8 被引用数 (Scopus)

抄録

Minimum Classification Error (MCE) training, which can be used to achieve minimum error classification of various types of patterns, has attracted a great deal of attention. However, to increase classification robustness, a conventional MCE framework has no practical optimization procedures like geometric margin maximization in Support Vector Machine (SVM). To realize high robustness in a wide range of classification tasks, we derive the geometric margin for a general class of discriminant functions and develop a new MCE training method that increases the geometric margin value. We also experimentally demonstrate the effectiveness of our new method using prototype-based classifiers.

本文言語English
ホスト出版物のタイトル2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 - Proceedings
ページ2170-2173
ページ数4
DOI
出版ステータスPublished - 2010 11月 8
外部発表はい
イベント2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 - Dallas, TX, United States
継続期間: 2010 3月 142010 3月 19

出版物シリーズ

名前ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN(印刷版)1520-6149

Conference

Conference2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010
国/地域United States
CityDallas, TX
Period10/3/1410/3/19

ASJC Scopus subject areas

  • ソフトウェア
  • 信号処理
  • 電子工学および電気工学

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