重庆理工大学学报：自然科学2012，Vol.26Issue(12)：93-98,6.
基于ν-最大间隔超球体支持向量机的非平衡数据分类
Classification of Imbalanced Data Based on Nu-maximum Margin Hyper Sphere Support Vector Machine
李秋林1
作者信息
- 1. 西南大学数学与统计学院,重庆400715
- 折叠
摘要
Abstract
In view of the traditional HSSVM(hyper sphere support vector machine) in processing of imbalanced data set the minority class the problem of low recall ratio,and by introducing the maximum margin and the parameter nu,this paper proposed the NU-MMHSSVM(nu-maximum margin hyper sphere support vector machine).The algorithm takes the maximum margin as the optimization target to build a classification model,greatly improving the minority class recall.Through UCI data set classification experiments,the algorithm with the traditional HSSVM(hyper sphere support vector machine) classification accuracy is compared.The results show that the algorithm can effectively improve the imbalanced distribution of data classification accuracy.关键词
支持向量机/超球体支持向量机/最大间隔/非均衡数据Key words
support vector machine/hyper sphere support vector machine/maximum margin/imbalanced data分类
信息技术与安全科学引用本文复制引用
李秋林..基于ν-最大间隔超球体支持向量机的非平衡数据分类[J].重庆理工大学学报：自然科学,2012,26(12):93-98,6.
