Minimal Complexity Support Vector Machines for Pattern Classification

Minimal complexity machines (MCMs) minimize the VC (Vapnik-Chervonenkis) dimension to obtain high generalization abilities. However, because the regularization term is not included in the objective function, the solution is not unique. In this paper, to solve this problem, we discuss fusing the MCM...

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Hlavní autor:	Shigeo Abe
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	MDPI AG 2020-11-01
Edice:	Computers
Témata:	least squares support vector machines margin distributions minimum complexity machines pattern classification support vector machines VC dimension
On-line přístup:	https://www.mdpi.com/2073-431X/9/4/88
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