%0 Journal Article
%T Fast Weighted Support Vector Machine Training Algorithm<br>一种快速加权支持向量机训练算法
%A QIN Yu-ping
%A AI Qing
%A LIU Wei-jiang
%A <br>秦玉平
%A 艾青
%A 刘卫江
%J 计算机应用研究
%D 2007
%I 
%X This paper proposed a new traning algorithm of W-SVM that uses second-order information of objective function to select working set and deduced its KKT optimization condition.The experimental results show that the algorithm reduces the number of iterations,comparing with the training algorithm that uses first-order approximate information of objective function to select working set,especially when the training set is very large,its convergence rate is speeded up highly.
%K weighted support vector machine(W-SVM)
%K working set
%K objective function<br>加权支持向量机
%K 工作集
%K 目标函数
%K 快速
%K 加权支持向量机
%K 训练算法
%K Algorithm
%K Training
%K Support
%K Vector
%K Machine
%K Weighted
%K 收敛速度
%K 规模
%K 训练集
%K 迭代次数
%K 一阶近似
%K 结果
%K 实验
%K 条件
%K 工作集
%K 信息选择
%K 二阶
%K 目标函数
%K 利用
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=C793235A4E87B8F663DFE198648D1DB0&yid=A732AF04DDA03BB3&vid=B91E8C6D6FE990DB&iid=DF92D298D3FF1E6E&sid=9971A5E270697F23&eid=339D79302DF62549&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=11