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一种基于L2范数的软核感知机
引用本文:王健,石尉,陶卿. 一种基于L2范数的软核感知机[J]. 计算机工程与应用, 2007, 43(2): 91-94
作者姓名:王健  石尉  陶卿
作者单位:中国人民解放军炮兵学院二系,合肥,230031;中国人民解放军炮兵学院二系,合肥,230031;中国人民解放军炮兵学院二系,合肥,230031
摘    要:感知机只能解决线性可分问题。支持向量机中的L2范数软边缘算法可以将线性不可分问题转化为线性可分问题。基于这一事实,提出一种基于L2范数的软核感知机(SoftKernelPerceptron,SKP),将感知机算法直接用于求解L2范数软边缘算法决定的线性可分问题。通过使用核技巧,得到一种普适的非线性分类方法。实际数据库的测试结果表明,SKP算法能够有效地解决非线性问题,并且继承了感知机运算简单速度快的优点。

关 键 词:感知机  核函数  线性可分  线性不可分  L2范数
文章编号:1002-8331(2007)02-0091-04
修稿时间:2006-05-01

Soft kernel perceptron in terms of L2 norm
WANG Jian,SHI Wei,TAO Qing. Soft kernel perceptron in terms of L2 norm[J]. Computer Engineering and Applications, 2007, 43(2): 91-94
Authors:WANG Jian  SHI Wei  TAO Qing
Affiliation:Department 2,New Star Research Inst.of Applied Teeh.,Heifei 230031,China
Abstract:The perceptron can only solve linearly separable problems.The L2 norm soft margin algorithms in SVMs can change each linearly inseparable problem into a separable one.Based on this fact,we propose a Soft Kernel Perceptron(SKP) in terms of L2 norm,in which the regular perceptron is directly employed to solve the linearly separable problem determined by L2 norm soft margin algorithms.By using kernel technique,a general method for solving nonlinear classifications is obtained.The experiments on some real datasets demonstrate that the proposed SKP can solve nonlinear classification efficiently.Moreover,it has the original advantage of simple calculation and fast speed.
Keywords:perceptron   kernel function   linearly separable   linearly inseparable   L2 norm
本文献已被 CNKI 维普 万方数据 等数据库收录!
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