Hypercuboid and hypersphere class least covers are used to be rules of constructing binary tree 所以，该算法采用最小超立方体和最小超球体类包含作为二叉树的生成算法。
2.
Theorem 1 . 4 let m be a hypersurface with non - zero constant scalar curvature in rn + l spanning a sphere sn - 1 ( r ) . if its gauss image lies in the semisphere , then m is a hypersphere cap )为边界的紧致常纯量曲率(非零)超曲面，如果其高斯映照像落在一个以s ~ ( n - 1 ) ( r )为边界的半球面内，则m只有超球面盖。
3.
The method , originally suggested by vapnik , interpreted as a novelty detectors by tax and duin . in was used as a classifier . it contains support vectors describing the hypersphere separating the samples 支持向量区域描述算法的主要思想是建立一个超球，包含所有同类点，目标函数使球半径尽量小，并且球内包含尽量多的同类点。
4.
Normal behavior and anomaly are distinguished on the basis of observed datum such as network flows and audit records of host . when a training sample set is unlabelled and unbalanced , attack detection is treated as outlier detection or density estimation of samples and one - class svm of hypersphere can be utilized to solve it . when a training sample set is labelled and unbalanced so that the class with small size will reach a much high error rate of classification , a weighted svm algorithm , i 针对训练样本是未标定的不均衡数据集的情况,把攻击检测问题视为一个孤立点发现或样本密度估计问题,采用了超球面上的one - classsvm算法来处理这类问题;针对有标定的不均衡数据集对于数目较少的那类样本分类错误率较高的情况,引入了加权svm算法-双v - svm算法来进行异常检测;进一步,基于1998darpa入侵检测评估数据源,把两分类svm算法推广至多分类svm算法,并做了多分类svm算法性能比较实验。
