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Fisher's Linear Discriminant Analysis (FLDA) uses the parametric form of the scatter matrix which is based on the Gaussian distribution assumption, and requires the scatter matrices to be nonsingular, which can not always be satisfied. To overcome this problem, many scholars have recently proposed Non-parametric Discriminant Analysis (NPDA), addressing the(More)
We first introduce the concepts of (λ, µ)-fuzzy subhyperlattices and (λ, µ)-fuzzy ideals. Secondly, we list some equivalent conditions of them. Lastly, we prove that the Cartesian product of two (λ, µ)-fuzzy subhyperlattices is still a (λ, µ)-fuzzy subhyperlattice. This paper can be seen as a generalization of [1].
This paper proposes a novel nonparametric discriminant analysis criterion, named weighted marginal discriminant analysis (WMDA), whose purpose is to efficiently utilize the marginal information of sample distribution in the discriminant analysis. The local mean is calculated by using the data points near the margin with different weights. The more(More)
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