Kernel Reverse Neighborhood Discriminant Analysis

Kernel Reverse Neighborhood Discriminant Analysis

Currently, neighborhood linear discriminant analysis (nLDA) exploits reverse nearest neighbors (RNN) to avoid the assumption of linear discriminant analysis (LDA) that all samples from the same class should be independently and identically distributed (i.i.d.). nLDA performs well when a dataset cont...

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Bibliographic Details
Main Authors: Wangwang Li, Hengliang Tan, Jianwei Feng, Ming Xie, Jiao Du, Shuo Yang, Guofeng Yan
Format: Article
Language:English
Published: MDPI AG 2023-03-01
Series:Electronics
Subjects:
linear discriminant analysis
kernel trick
reverse nearest neighbors
Gaussian kernel
Online Access:https://www.mdpi.com/2079-9292/12/6/1322

Internet

https://www.mdpi.com/2079-9292/12/6/1322

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