Discriminant Analysis

Ke-Lin Du () and M. N. S. Swamy
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Ke-Lin Du: Concordia University, Department of Electrical and Computer Engineering
M. N. S. Swamy: Concordia University, Department of Electrical and Computer Engineering

Chapter Chapter 16 in Neural Networks and Statistical Learning, 2019, pp 483-501 from Springer

Abstract: Abstract Discriminant analysis plays an important role in statistical pattern recognition. LDA, originally derived by Fisher, is one of the most popular discriminant analysis techniques. Under the assumption that the class distributions are identically distributed Gaussians, LDA is Bayes optimalBayes optimal. Like PCA, LDA is widely applied to image retrieval, face recognition, information retrieval, and pattern recognition. This chapter is dedicated to discriminant analysis.

Date: 2019
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DOI: 10.1007/978-1-4471-7452-3_16

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