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Lecture
Fitting and Clustering Data with Mixture of Gauss Functions
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.
Official source
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