Optimal Double-Kernel Combination Method for Classification

WANG Feng; ZHANG Hong-Bin

doi:10.3969/j.issn.0372-2112.2012.02.009

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Optimal Double-Kernel Combination Method for Classification

更新时间：2025-07-16

- Optimal Double-Kernel Combination Method for Classification
- Acta Electronica Sinica Vol. 40, Issue 2, Pages: 260-265(2012)
- 作者机构：
  
  北京工业大学计算机学院,北京,100124
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.0372-2112.2012.02.009
  CLC： TP391
- Published：2012
- 稿件说明：
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WANG Feng, ZHANG Hong-Bin. Optimal Double-Kernel Combination Method for Classification[J]. Acta Electronica Sinica, 2012, 40(2): 260-265.
DOI：

WANG Feng, ZHANG Hong-Bin. Optimal Double-Kernel Combination Method for Classification[J]. Acta Electronica Sinica, 2012, 40(2): 260-265. DOI： 10.3969/j.issn.0372-2112.2012.02.009.

摘要

由于使用单一且固定的核函数

传统的核分类算法不能有效地适应复杂的数据集合

导致分类性能下降.本文提出一种基于双核复合的分类算法ODKC(Optimal Double-Kernel Combination)的构造框架

通过融合两个基本核函数的映射来构造目标核函数.研究了双核复合的三种典型方式

并把这三种复合方式纳入到统一的框架下处理.论文以核与数据的匹配性度量KTA(Kernel Target Alignment)以及分类性能验证了所提算法的有效性.

Abstract

Traditional kernelised classification methods could not perform well sometimes because of using a single and fixed kernel

especially on some complicated data sets.In this paper

a novel optimal double-kernel combination (ODKC) method is proposed for complicated classification tasks.Firstly

data are mapped by two basic kernels into different feature spaces respectively

and then three kinds of optimal composite kernels are constructed by integrating information of the two feature spaces.Comparative experiments demonstrate the effectiveness of our methods.

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