Research on Piecewise Combination Support Vector Machine Based on Data Distribution Rules

CHEN Peng; LIU Shuang; ZUO Li; LI Xi-zuo

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Research on Piecewise Combination Support Vector Machine Based on Data Distribution Rules

更新时间：2026-09-04

- Research on Piecewise Combination Support Vector Machine Based on Data Distribution Rules
- Vol. 32, Issue 3, Pages: 94-99(2015)
- 作者机构：
  
  1. 1 大连东软信息学院机构计算机科学与技术系,辽宁,大连,116023
  2. 2 大连民族学院计算机科学与工程学院,辽宁,大连,116600
  3. 3 大连民族学院经济管理学院,辽宁,大连,116600
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2015
- 稿件说明：
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陈鹏, 刘爽, 左莉, 李锡祚. 基于数据分布规律的分段组合支持向量机研究[J]. 微电子学与计算机, 2015, 32(3): 94-99.

CHEN Peng, LIU Shuang, ZUO Li, et al. Research on Piecewise Combination Support Vector Machine Based on Data Distribution Rules[J]. 2015, 32(3): 94-99.
陈鹏, 刘爽, 左莉, 李锡祚. 基于数据分布规律的分段组合支持向量机研究[J]. 微电子学与计算机, 2015, 32(3): 94-99. DOI：

CHEN Peng, LIU Shuang, ZUO Li, et al. Research on Piecewise Combination Support Vector Machine Based on Data Distribution Rules[J]. 2015, 32(3): 94-99. DOI：

摘要

在分析数据分布规律的基础上

提出了分段组合支持向量机算法.该算法首先统计数据分布规律

采用均值聚类计算聚类中心

然后分球形分布、线性二分可分、局部线性二分可分三种情况来组织最小包含最大排除球目标函数、普通核函数、局部线性核函数

从而实现对不同的数据分布采用不同的支持向量机分类决策算法

提高算法的分类性能.

Abstract

Based on analysis of data distribution rules

piecewise combination support vector machine is put forward in this paper. First

statistical analysis is adopted for the original data. Then

-means cluster algorithm is introduced to compute cluster centers for the data. For three cases of data distribution

which is

sphere-distribution

linearly binary separable distribution

and locally linearly separable distribution

minimum enclosing and maximum excluding support vector machine

common support vector machine and local linear support vector machine are defined to solve the objective problems. Different support vector machines for different data distribution will improve classification performance.

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