LDA and QDA for Classification

May 13, 2021

Discriminant analysis encompasses methods that can be used for both classification and dimensionality reduction. Linear discriminant analysis (LDA) is particularly popular because it is both a classifier and a dimensionality reduction technique. Despite its simplicity, LDA often produces robust, decent, and interpretable classification results. When tackling real-world classification problems, LDA is often the first and benchmarking method before other more complicated and flexible ones are employed. Quadratic discriminant analysis (QDA) is a variant of LDA that allows for non-linear separation of data.