Scaling Kernel Function Support Vector Machines

ZHANG Li; ZHOU Wei-da; JIAO Li-cheng

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Scaling Kernel Function Support Vector Machines

更新时间：2025-07-16

- Scaling Kernel Function Support Vector Machines
- Acta Electronica Sinica Vol. 30, Issue 4, Pages: 527-529(2002)
- 作者机构：
  
  西安电子科技大学雷达信号处理重点实验室,陕西,西安,710071
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP391.4
- Published：2002
- 稿件说明：
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ZHANG Li, ZHOU Wei-da, JIAO Li-cheng. Scaling Kernel Function Support Vector Machines[J]. Acta Electronica Sinica, 2002, 30(4): 527-529.
DOI：

ZHANG Li, ZHOU Wei-da, JIAO Li-cheng. Scaling Kernel Function Support Vector Machines[J]. Acta Electronica Sinica, 2002, 30(4): 527-529. DOI：

摘要

本文提出了一种可容许的支撑矢量机核—尺度核.该尺度核函数可以被看作是一个具有平移因子的多维尺度函数

它能作为平方可积空间的子空间上一组完备的基函数.在此意义上

采用尺度核函数的支撑矢量机

可以认为是在尺度空间中寻找最佳的尺度系数.因此在理论上尺度核函数支撑矢量机能够以零误差逼近某一空间上的任何目标函数

文中给出的仿真实验进一步验证了它的可行性和有效性.

Abstract

A kind of admissible support vector kernel called scaling kernels are presented in this paper.In fact

scaling kernels are the multi-dimensional scaling function with translation vectors and they are a set of complete bases in the sub-space of the square and integrable space.Hence

the goal of scaling kernel function support vector machines is to find the optimal scaling coefficients in a scaling space.In terms of theory

scaling kernel function SVMs can approximate any objective function in some space by any precision.The results obtained by our simulations show the feasibility and validity of scaling kernels.

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Related Institution

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