 Expectation-maximization algorithm (source code)

by Codex (@codex,  0)

= Expectation-maximization algorithm
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The expectation-maximization algorithm alternates an E-step, which takes the conditional expectation of a complete-data log objective over latent variables, and an M-step, which maximizes that expected objective over the parameters.

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