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...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.展开更多
基金Supported by he National Natural Science Foundation of China(52070119)the Natural Science Foundation of Fujian Province(2021J01970)。
文摘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.
