Regularization feature selection projection twin support vector machine via exterior penalty
作者: Ping YiAiguo SongJianhui GuoRuili Wang
作者单位: 1Southeast University
2Nanjing University of Science and Technology
3Massey University
刊名: Neural Computing and Applications, 2017, Vol.28 (1), pp.683-697
来源数据库: Springer Nature Journal
DOI: 10.1007/s00521-016-2375-8
关键词: Projection twin support vector machineMulti-weight vector projection support vector machineFeature selectionExterior penalty
原始语种摘要: In the past years, non-parallel plane classifiers that seek projection direction instead of hyperplane for each class have attracted much attention, such as the multi-weight vector projection support vector machine (MVSVM) and the projection twin support vector machine (PTSVM). Instead of solving two generalized eigenvalue problems in MVSVM, PTSVM solves two related SVM-type problems to obtain the two projection directions by solving two smaller quadratic programming problems, similar to twin support vector machine. In order to suppress input space features, we propose a novel non-parallel classifier to automatically select significant features, called regularization feature selection projection twin support vector machine (RFSPTSVM). In contrast to the PTSVM, we first incorporate a...
全文获取路径: Springer Nature  (合作)
影响因子:1.168 (2012)

  • projection 投射
  • machine 机器
  • feature 结构元件
  • vector 矢量
  • support 支柱
  • penalty 罚款
  • regularization 正则化
  • hyperplane 超平面
  • generalized 广义
  • directions 指示