首页 | 本学科首页   官方微博 | 高级检索  
     

支持向量机及其在模式识别中的应用
引用本文:刘向东,朱美琳,陈兆乾,陈世福.支持向量机及其在模式识别中的应用[J].计算机科学,2003,30(6):113-117.
作者姓名:刘向东  朱美琳  陈兆乾  陈世福
作者单位:南京大学计算机科学与技术系,南京大学计算机软件新技术国家重点实验室,南京,210093
摘    要:Statistical learning theory(SLT)and support vector machine(SVM) are effective to solve problems of machine learning under the condition of finite samples.It is known that the performance of support vector machine is often better than that of some neural networks in pattern recognition,especially in high dimensional space,and they arewell used in many domains for recognition.This paper at first introduces the basic theory of SLT and SVM,then points out the key problems of SVM and its research situation in recent years,and at last describes some applications of SVM in the field of pattern recognition.

关 键 词:机器学习  支持向量机  模式识别  统计学习理论

Support Vector Machine and its Applications in Pattern Recognition
LIU Xiang-Dong ZHU Mei-Lin CHEN Zhao-Qian CHEN Shi-Fu.Support Vector Machine and its Applications in Pattern Recognition[J].Computer Science,2003,30(6):113-117.
Authors:LIU Xiang-Dong ZHU Mei-Lin CHEN Zhao-Qian CHEN Shi-Fu
Abstract:Statistical learning theory(SLT) and support vector machine(SVM) are effective to solve problems of machine learning under the condition of finite samples. It is known that the performance of support vector machine is often better than that of some neural networks in pattern recognition,especially in high dimensional space,and they are well used in many domains for recognition. This paper at first introduces the basic theory of SLT and SVM,then points out the key problems of SVM and its research situation in recent years,and at last describes some applications of SVM in the field of pattern recognition.
Keywords:Support vector machine  Classification  Machine learning  Pattern recognition  
本文献已被 CNKI 维普 万方数据 等数据库收录!
点击此处可从《计算机科学》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号