Lecture

Fitting and Clustering Data with Mixture of Gauss Functions

In course

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Description

This lecture covers the concept of Mixture of Gauss Functions, explaining the density of mixture, linear weighted combination, and the expectation-maximization (E-M) algorithm. It also discusses Gaussian Mixture Modeling with E-M, hyper-parameter optimization, and the tradeoff between computation costs and better fit.

Instructor

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Official source

https://mediaspace.epfl.ch/media/0_cgc5sxzd

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Ontological neighbourhood

Information engineering

Machine learning: Unsupervised learning

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