Geometrical properties of Nu support vector machines with different norms

Kazushi Ikeda; Noboru Murata

doi:10.1162/0899766054796897

Geometrical properties of Nu support vector machines with different norms

Kazushi Ikeda^*, Noboru Murata

^*この研究の対応する著者

先進理工学部

研究成果: Article › 査読

19 被引用数 (Scopus)

抄録

By employing the L₁ or L_∞ norms in maximizing margins, support vector machines (SVMs) result in a linear programming problem that requires a lower computational load compared to SVMs with the L₂ norm. However, how the change of norm affects the generalization ability of SVMs has not been clarified so far except for numerical experiments. In this letter, the geometrical meaning of SVMs with the L_p norm is investigated, and the SVM solutions are shown to have rather little dependency on p.

本文言語	English
ページ（範囲）	2508-2529
ページ数	22
ジャーナル	Neural Computation
巻	17
号	11
DOI	https://doi.org/10.1162/0899766054796897
出版ステータス	Published - 2005 11月 1

ASJC Scopus subject areas

人文科学（その他）
認知神経科学

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10.1162/0899766054796897

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Geometrical properties of Nu support vector machines with different norms

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