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This lecture covers the Gaussian Discriminant Rule for classification in machine learning, focusing on the use of Gaussian Mixture Models (GMM) with different covariance matrices. It explains how to determine class labels and boundaries using ML discriminant rules. Practical exercises involve drawing boundaries for GMMs and understanding the impact of model complexity on classification accuracy.
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