Linear Discriminant Analysis

Andreas Tilevik
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Andreas Tilevik: University of Skövde

Chapter Chapter 7 in Multivariate Statistics and Machine Learning in R For Beginners, 2025, pp 111-117 from Springer

Abstract: Abstract This chapter shows how to compute linear discriminant analysis (LDA), a statistical technique used for classification and dimensionality reduction. Unlike PCA, which aims to find a linear combination of variables that maximizes variance, LDA seeks a linear combination that best separates the classes in the dataset. To understand how LDA works, we will first calculate it “by hand” in R and then use the lda function to perform the same calculations with a single line of code.

Date: 2025
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DOI: 10.1007/978-3-032-01851-9_7

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