【作者】 闫志刚； 杜培军；

【Author】 Yan Zhigang1,2 Du Peijun1(1School of Environment Science and Spatial Informatics,China University of Mining and Technology,Xuzhou 221116,China) (2 State Key Laboratory for Geomechanics and Deep Underground Engineering,China University of Mining and Technology,Xuzhou 221008,China)

【机构】 中国矿业大学环境与测绘学院； 中国矿业大学深部岩土力学与地下工程国家重点实验室；

【摘要】 通过推导H-SVMs推广能力的模型,得出H-SVMs的推广能力与样本类别数、空间分布、容量、树结构等有关,且保证高优先级结点的推广性能是提高H-SVMs性能的有效途径。根据分析结果,提出了一种基于SVM最大间隔分类、最小间隔聚类构造H-SVMs的新方法。利用SVM的分类间隔作为分类、聚类指标,通过Top-down和Bottom-up两种途径混合构造H-SVMs,其中,最大间隔分类采用Top-down策略,在各结点依次选择最大间隔的SVM,将输入样本按类别分为2类;最小间隔聚类采用Bottom-up策略,在各结点依次选择最小间隔的SVM,将输入样本按类别两两聚类。从UCI数据库中选取多类数据进行测试,实验结果验证了该方法的有效性,说明所构造的H-SVMs具有较好的、稳定的推广性能。更多还原

【Abstract】 By deducing the formula for the generalization power of hierarchical support vector machines(H-SVMs),it can be concluded that the generalization power of H-SVMs is related to the count,the distribution,the capacity of the input samples and H-SVMs’ structure.And the guarantee of the generalization ability of the SVM node,whose position is located at a high level,can improve the performance of H-SVMs.Then,a novel method for building H-SVMs is put forward.The separation distances of SVMs are regarded as the indices for classifying and clustering.Through the top-down and bottom-up routes,the input samples are classified by maximal separation distances and clustered by minimal separation distance.The approach of classification by maximal separation distance can select the SVM whose separation margin is maximal based on the top-down route,and dichotomize the input samples according to their categories at each node.The approach of clustering by minimal separation distance can select the SVM whose separation margin is minimal based on the bottom-up route,and hierarchically cluster every two input samples according to their categories at each node.Several multiclass data sets from UCI database are selected to test this method.The experimental results show that the method is practicable,and the corresponding H-SVMs structure has a preferable and stable generalization ability.更多还原