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This lecture covers Linear Discriminant Analysis (LDA) as a generative method for classification. It describes how LDA approximates the optimal Bayes classifier by estimating prior probabilities and assuming Gaussian distributions. The lecture also discusses discriminative models like Fisher discriminant analysis and logistic regression, highlighting supervised learning procedures.