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pro vyhledávání: '"Xu Chan Ju"'
Autor:
Ying-Jie Tian, Xu-Chan Ju
Publikováno v:
Journal of the Operations Research Society of China. 3:499-519
In this paper, we present a novel nonparallel support vector machine based on one optimization problem (NSVMOOP) for binary classification. Our NSVMOOP is formulated aiming to separate classes from the largest possible angle between the normal vector
Autor:
Ying Jie Tian, Xu Chan Ju
Publikováno v:
2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology.
In this paper, we proposed a novel nonparallel hyper planes classifier for binary classification, termed as NHC. Though this method can be in fact proved equivalent to an improved twin support vector machine (TWSVM), it has the incomparable advantage
Autor:
Ying Jie Tian, Xu Chan Ju
Publikováno v:
ICDM Workshops
In this paper we proposed a novel knowledge based twin support vector machine (TWSVM), in which the prior knowledge in the form of multiple polyhedral sets, each belonging to one of two categories, is incorporated into the Linear TWSVM. Different wit