【摘要】 支持向量机 (SVM)方法就是利用最优分类面 (线 )将两类样本在特征空间或输入空间中无错误地分开 ,而且要使两类的分类空隙最大。因此标准的SVM方法需要求解二次规划问题 ,计算量很大 ,本文介绍一种方法解决这个问题 ,并成功地将该算法应用于医学图像数据挖掘的分类问题更多还原

【Abstract】 Support vector machine(SVM) is to correctly classify samples into two parallel planes in input or feature space by optimal planes(lines),and the margin between the two classes is made to be the largest.The standard SVM requires solving quadratic program that needs considerably longer computational time.An algorithm is introduced to solve the problem in this paper,which is successfully applied to the classification of medical image data mining.更多还原