Lecture

Gaussian Discriminant Rule: Classification & Boundaries

Description

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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Official source

https://mediaspace.epfl.ch/media/0_ughspg78

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Ontological neighbourhood

Information engineering

Machine learning: Topics in machine learning, Artificial neural networks

Statistics

Statistical inference: Mathematical statistics

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