Nonlinear Discriminant Analysis Method Based on the Class Cover and Its Application  

作　　者：Liwen HUANG 

机构地区：[1]College of Mathematics and Computer Science,Quanzhou Normal University,Quanzhou 362000,China

出　　处：《Journal of Systems Science and Information》2023年第6期761-775,共15页系统科学与信息学报（英文）

基　　金：Supported by he National Natural Science Foundation of China(52070119);the Natural Science Foundation of Fujian Province(2021J01970)。

摘　　要：This paper introduces the related concepts of the hybrid spherical-shaped dataset and proposes a new discriminant analysis method based on the spherical-shaped dataset (SDAM), then SDAM is further improved by the idea of the class cover and presents the nonlinear discriminant analysis method (NDAM). To demonstrate the effectiveness of these two methods, this work constructs seven hybrid spherical-shaped datasets and uses nine UCI datasets. Numerical experiments on these examples indicate that SDAM can preferably solve the discriminant problem for the hybrid sphericalshaped dataset, but this method does not always work well for real datasets;NDAM overcomes the drawbacks of SDAM and better solves the discriminative problem of real datasets. Besides, it has better stability.

关 键 词：nonlinear discriminant analysis discriminant rule class cover hybrid spherical-shaped dataset 

分 类 号：O212.1[理学—概率论与数理统计]