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When you try to approximate your data with a mixture of distributions, say Gaussians for instance, you have to initialize their parameters with some values befo
by kleene_op 5y ago
When you try to approximate your data with a mixture of distributions, say Gaussians for instance, you have to initialize their parameters with some values before running your EM loop.
Finding good ones can be very problematic. The k-means process is a reasonable method to get good enough starting values without having to think/compute too much.
https://en.wikipedia.org/wiki/Expectation%E2%80%93maximization_algorithm https://en.wikipedia.org/wiki/Expectation%E2%80%93maximizati...
- civilized 5y agoOK, so for you, "bootstrapping statistical mixtures" means "warm-starting EM mixture modeling". Personally I never would have guessed that, in retrospect it makes sense... to each their own!