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In Statistics, an expectation–maximization (EM) algorithm is an iterative method for finding Maximum likelihood or maximum a posteriori (MAP) estimates of parameters in statistical models, where the model depends on unobserved latent variables. (https://en.wikipedia.org/wiki/Expectation–maximization_algorithm)

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