Linear Discriminant Analysis (LDA)

Linear Discriminant Analysis (LDA) is a technique used in machine learning and pattern recognition to reduce dimensionality and classify data. It seeks linear combinations of features that best distinguish various classes in the data while reducing variance within each class. LDA works well for tasks like classification, clustering, and feature extraction, particularly in high-dimensional data.

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