Neighborhood linear discriminant analysis
Abstract
Linear Discriminant Analysis (LDA) assumes that all samples from the same class are independently and identically distributed (i.i.d.). LDA may fail in the cases where the assumption does not hold. Particularly when a class contains several clusters (or subclasses), LDA cannot correctly depict the internal structure as the scatter matrices that LDA relies on are defined at the class level. In order to mitigate the problem, this paper proposes a...
Paper Details
Title
Neighborhood linear discriminant analysis
Published Date
Mar 1, 2022
Journal
Volume
123
Pages
108422 - 108422
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