| 基于支持向量机的粗糙分类器 |
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| 引用本文： | 梁锦锦,时海亮,刘三阳,石莎. 基于支持向量机的粗糙分类器[J]. 计算机工程与设计, 2007, 28(19): 4729-4731 |
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| 作者姓名： | 梁锦锦 时海亮 刘三阳 石莎 |
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| 作者单位： | 西安电子科技大学,数学科学系,陕西,西安,710071;郑州轻工业学院,信息与计算科学系,河南,郑州,450002;西安电子科技大学,计算机学院,陕西,西安,710071 |
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| 摘 要： | 支持向量机和粗糙集理论是两种分类技术.前者寻求最大化两类间隔的最优分类超平面,后者用逻辑规则解释分类.基于两者的关系,提出了一种复合算法,且将其推广到回归.新算法在一定程度降低了计算复杂度,且适用于软间隔分类.数值实验表明新算法是有效可行的.
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| 关 键 词： | 支持向量机 粗糙集 分类 最大化间隔 逻辑规则 软间隔 |
| 文章编号： | 1000-7024（2007）19-4729-03 |
| 修稿时间： | 2006-10-19 |
Rough classifier based on support vector machine |
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| LIANG Jin-jin,SHI Hai-liang,LIU San-yang,SHI Sha. Rough classifier based on support vector machine[J]. Computer Engineering and Design, 2007, 28(19): 4729-4731 |
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| Authors: | LIANG Jin-jin SHI Hai-liang LIU San-yang SHI Sha |
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| Abstract: | Support vector machine(SVM) and rough set(RS) theory are two classification techniques.The former attempts to find an optimal hyperplane that maximize margin between two classes,and the later are designed to provide an explanation of the classification using logical rules.A compact algorithm is proposed based on the relationship between their principles.This new algorithm can reduce the complexity of computation to a certain degree and is especially useful for soft margin classifier;also it is generalized to regression.Numerical results illustrate that the algorithm is feasible and effective. |
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| Keywords: | support vector machine rough set theory classification maximize margin logical rules soft margin |
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